bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-17. A DEEP LEARNING MODEL FOR DISCRIMINATING TRUE PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMA PATIENTS
Authors: Moassefi Mana , Faghani Shahriar , Conte Gian Marco , Kowalchuk Roman , Vahdati Sanaz , Crompton David , Vega Carlos Perez , Cabreja Ricardo Domingo , Vora Sujay , Quiñones-Hinojosa Alfredo , Parney Ian , Trifiletti Daniel , Erickson Bradley 
Published: November 2022

Abstract

INTRODUCTION
Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease.

METHOD
We included newly diagnosed GBM patients who met the inclusion criteria, including a new or increasing enhancing lesion size within the original radiation field and who had clinical, medication, and any histopathology available. The interpretation of the MR images at the image inclusion time point had to be indeterminate. We labeled those who subsequently were stable or improved on imaging and clinically as PSP and those with clinical and imaging deterioration as TP. A subset of subjects underwent a second resection. We labeled these subjects as PSP or TP based on the histological diagnosis. We performed skull stripping, coregistered contrast-enhanced T1 MRIs with T2-weighted images for each patient and used them as input to a 3-D Densenet121 model. We used several augmentation techniques and five-fold cross-validation to achieve more robust predictions.

RESULT
We included 124 patients who met the criteria, and of those, 63 were PsP and 61 were TP. We trained a deep learning model that achieved 76.4% (ranged 70%-84%, SD 5.122) mean accuracy over the 5 folds, 0.7560(ranged 0.6553-0.8535, SD 0.069) mean AUROCC, 88.72% (SD 6.86) mean sensitivity, and 62.05%(SD 9.11) mean specificity.

CONCLUSION
We report the development of a deep learning model that distinguishes PsP from TP in GBM patients treated per the Stupp protocol. Further refinement and external validation are required prior to widespread adoption in clinical practice.
NIMG-20. INCORPORATION OF AI-BASED AUTOSEGMENTATION AND CLASSIFICATION INTO NEURORADIOLOGY WORKFLOW: PACS-BASED AI TO BUILD YALE GLIOMA DATASET
Authors: Lost Jan , Tillmans Niklas , Merkaj Sara , von Reppert Marc , Lin MingDe , Bousabarah Khaled , Huttner Anita , Aneja Sanjay , Omuro Antonio , Aboian Mariam , Avesta Arman 
Published: November 2022

Abstract

PURPOSE
Translation of AI algorithms into clinical practice is significantly limited by lack of large individual hospital-based datasets with expert annotations. Current methods for generation of annotated imaging data are significantly limited due to inefficient imaging data transfer, complicated annotation software, and time required for experts to generate ground truth information. We incorporated AI tools for auto-segmentation of gliomas into PACS that is used at our institution for reading clinical studies and developed a workflow for annotation of images and development of volumetric segmentations in neuroradiology clinical workflow. Material: 1990 patients from Yale Radiation Oncology Registry (2012-2019) were identified. Segmentations were performed using a UNETR algorithm trained on BRaTS 2021 and an internal dataset of manually segmented tumors. Segmentations were validated by a board-certified neuro-radiologist and natively embedded PyRadiomics in PACS was used for feature extraction.

RESULTS
In 7 Months (05/2021 - 08/2021, 03/2022 - 05/2022) segmentations and annotations were performed in 835 patients (322 female, 467 male, 46 unknown, mean age 53 yrs). Dataset includes 275 Grade 4 Gliomas (54 Grade 3, 100 Grade 2, 31 Grade 1, 375 unknown). Molecular subtypes include IDH (113 mutated, 498 wildtype, 2 Equivocal, 222 unknown), 1p/19q (87 deleted or co-deleted, 122 intact, 626 unknown), MGMT promotor (182 methylated, 95 partially methylated, 275 unmethylated, 283 unknown), EGFR (76 amplified, 177 not amplified, 582 unknown), ATRX (40 mutated, 157 retained, 638 unknown), Ki-67 (616 known, 219 unknown) and p53 (549 known, 286 unknown). Classification of gliomas between grade 3/4 and grade 1/2, yielded AUC of 0.85.

CONCLUSION
We developed a method for incorporation of volumetric segmentation, feature extraction, and classification that is easily incorporated into neuroradiology workflow. These tools allowed us to annotate over 100 gliomas per month, thus establishing a proof of concept for rapid development of annotated imaging database for AI applications.
NIMG-69. MRI T2 RELAXIVITY IN THE PREDICTION OF PROGRESSION-FREE SURVIVAL IN NEWLY-DIAGNOSED GLIOBLASTOMA: WHOLE BRAIN MEASUREMENTS AND DEEP LEARNING
Authors: Rulseh Aaron , Vymazal Josef 
Published: November 2022

Abstract
Glioblastoma (GBM) is the most common and aggressive primary brain tumour; we aimed to evaluate T2 relaxivity in their follow. Fifty-one newly diagnosed GBM followed at our department after surgery and combined chemo-radiotherapy were included (&gt; 180 days progression-free survival [PFS] as determined by RANO, ≥ 3 MRI examinations in the PFS interval). All data used were prior to progression. T2 relaxation rates (1/T2f) were calculated voxel-wise assuming mono-exponential decay. Whole-brain (WB) values were extracted including skewness, kurtosis, mean, median, 15 and 85 percentile histogram values and variance. We additionally segmented the 1/T2f volumes using a 5 compartment Gaussian mixture model, producing mean, variance and percent per component. To evaluate predictive potential with respect to PFS, we used a deep long short-term memory (LSTM) model in tensorflow (4 timesteps). Twenty subjects were included in the predictive model, as inclusion criteria differed (progression, ≤ 120 days between all MRIs [mean 44.3 days], ≥ 4 PFS MRIs). Two models were tested: a regression model (days to progression) and a classification model (±18 months PFS; models differed in output layer). Both models were run 10 times; mean results are presented. We found WB median 1/T2f correlated with PFS, as values decreased prior to progression. WB median 1/T2f linear regression slopes also differed in progression vs. pseudo-progression. The deep LSTM regression model achieved an R2 of 86%. The deep LSTM classification model achieved a mean macro precision of 85%, recall 84% and F1 accuracy of 84% in classifying progression/no progression at an 18 month cutoff. We found very intriguing results with WB median 1/T2f measurements in distinguishing progression from pseudo-progression, and in suggesting progression despite otherwise unremarkable imaging. A more complex predictive model, using a fully-automated segmentation method followed by deep learning, was very promising. Our results may find utility in the monitoring of GBM patients.
NIMG-70. MAGNETIC RESONANCE HYPOXIA IMAGING FOR RADIATION TREATMENT GUIDANCE IN GLIOBLASTOMA MULTIFORME - A DIAGNOSTIC/PROGNOSTIC CLINICAL IMAGING STUDY
Authors: Brighi Caterina , Waddington David , Keall Paul , Booth Jeremy , O'Brien Kieran , Parkinson Jonathon , Yim Jackie , Bailey Dale , Back Michael , Drummond James 
Published: November 2022

Abstract
Local recurrence in glioblastoma (GBM) patients is caused by the ability of tumour cells to develop treatment resistance mechanisms. Hypoxia, which is present in subregions of GBM tumours, is the leading cause of resistance to radiotherapy and is associated with worse clinical outcomes in GBM. Current standard of care treatment does not account for tumour hypoxia. The ability to image tumour hypoxia at various stages of treatment offers opportunities to personalise and improve treatment for GBM patients. Preoperative imaging of tumour hypoxia offers the opportunity for supramarginal resections in surgical planning beyond current neurosurgical standard of care guidelines. Imaging hypoxia prior to radiotherapy enables selective dose escalation strategies to radioresistant tumour regions, increasing the likelihood of local control. Identifying hypoxic tumour regions harbouring progression at follow up is key to intervening at an early stage of tumour recurrence and personalising therapy tailored to the tumour response to treatment. Imaging of tumour hypoxia in routine clinical practice is challenging, as it requires 18FMISO PET, which is not available in most clinical centres. In this clinical imaging study, we aim to investigate the role of oxygen enhanced (OE) and blood-oxygen level dependent (BOLD) MRI as imaging biomarkers of hypoxia in GBM. Aiming to recruit 20 GBM patients, this study involves the addition of OE/BOLD MRI and 18FMISO PET imaging at several timepoints during the course of treatment. The primary objective is to investigate the ability of OE/BOLD MRI to map tumour hypoxia on preoperative scans using 18FMISO PET as the ground truth. Secondary objectives include evaluating the role of hypoxia imaging biomarkers for dose-painting radiotherapy planning and treatment response assessment in GBM. Overall, by validating the role of MRI biomarkers of hypoxia we ought to provide a non-invasive and more accessible means to more effective, personalised treatment to GBM patients.
NIMG-76. MORPHOLOGIC CHANGES TO THE HIPPOCAMPI FOLLOWING SURGICAL RESECTION AND ADJUVANT CHEMORADIATION IN PATIENTS WITH HIGH GRADE TEMPORAL GLIOMAS
Authors: Fernandez Luis , Oyon Daniel , Gibson William , Behbahani Mandana , Khan Osaama , Sharma Shelly 
Published: November 2022

Abstract

BACKGROUND
The hippocampus is known to remodel in pathologic conditions including epilepsy and Alzheimer’s disease. Literature investigating the effect of high-grade gliomas (HGGs) on the hippocampus following resection and adjuvant chemoradiation are limited; no study has evaluated these effects in tumors exclusively in the temporal lobe.

METHODS
A retrospective chart review was conducted on 30 patients with temporal HGGs who underwent craniotomy for resection with adjuvant RT and TMZ. Brainlab Elements was used to manually contour bilateral hippocampal gray matter volumes in the subgranular zone using T1-precontrast MRI sequences (1.5 mm thickness or less) pre-resection and at time of most recent follow up. These volumes were compared using a student’s t-test with significance set at p&lt; 0.05.

RESULTS
Average follow up time was 23.5 months from initial resection. Average pre-treatment hippocampal volumes in this temporal glioma cohort compared to healthy controls from prior studies were 2.93 vs 2.83 cm3 (right, p=0.31) and 2.78 vs 2.76 cm3 (left, p=0.39) respectively. Pre vs post resection right hippocampal volumes in patients with right sided lesions were 2.59 vs 1.75 cm3 (p=.002). Left hippocampal volumes in patients with left sided tumors were 2.99 vs 1.64 cm3 pre and post resection respectively(p=0.0009). No significant differences in hippocampal volumes contralateral to the tumor side were found following treatment (p=0.31 and 0.07 for right and left hippocampi respectively).

CONCLUSIONS
Temporal gliomas are in close anatomic proximity to the hippocampi also may invade and/or disrupt local circuits which output to the hippocampi. Resection and chemoradiation are correlated with decreased hippocampal volumes ipsilateral to the primary locus of disease. Further characterization of hippocampal subregions, particularly the dentate gyrus, in addition to results of neuropsychiatric testing pre and post treatment are necessary to better elucidate the clinical implications of these morphologic changes and the putative functional networks which underlie them.
NIMG-93. CORRELATING RELATIVE LEVEL OF IMMUNOCOMPETENCE FOR CNS LYMPHOMA BY RADIOLOGIC CHARACTERISTICS: A CASE SERIES
Authors: Koduri Laila , Gupta Kanika , Katz Makenna , Trevino Christopher 
Published: November 2022

Abstract
Radiologically, central nervous system lymphoma (CNSL) presents differently in immunocompetent versus immunosuppressed states. Most patients with immunocompetent CNS lymphoma present with a solitary, deep, homogeneously enhancing lesion while patients with immunocompromised CNS lymphoma frequently have multifocal, centrally necrotic enhancing brain lesions. To date, there have been no radiologic features described along a spectrum of relative levels of immunocompetence. A single institution review on twelve patients with primary and secondary CNSL included clinical factors at diagnosis that are associated with varying levels of relative immunocompromised state. We collected qualitative data on age, prior cancer, radiation, chemotherapy, HIV, diabetes mellitus, steroid/immunosuppressant use, and quantifiable data including white blood cell, neutrophil, and lymphocyte counts. These factors were stratified for severity and correlated with findings on imaging. Our study identified patients with a minor level of immunocompromised state were more likely to develop multifocal disease, while patients with more severe immunocompromised states were likely to develop necrosis. Although our study is limited as a retrospective analysis, these findings suggest that the radiographic findings can present as a spectrum which can reflect a relative level of immunocompetence. This study warrants further evaluation in a larger and prospective cohort for validation.
NIMG-101. COMPARISON OF PRE-SURGICAL MRI FINDINGS FROM LONG-TERM (≥ 3 YRS) VERSUS SHORT-TERM (&lt; 3 YRS) GLIOBLASTOMA SURVIVORS: A BLINDED, CASE-CONTROL REVIEW
Authors: Komlodi-Pasztor Edina , Briceno Nicole , Vera Elizabeth , Choi Anna , Christ Alexa , Grajkowska Ewa , Leeper Heather , Lindsley Matthew , Wall Kathleen , Evans Karen , Kunst Tricia , Mentges Kelly , Reyes Jennifer , Boris Lisa , Burton Eric , Lollo Nicole , Panzer Marissa , Penas-Prado Marta , Pillai Valentina , Theeler Brett , Wu Jing , Polskin Lily , Armstrong Terri , Gilbert Mark , Smirniotopoulos James 
Published: November 2022

Abstract

BACKGROUND
The median overall survival of patients with glioblastoma (GBM) is 10-12 months and the five-year survival ranges from 5-10%. Favorable clinical and molecular prognostic markers have been described in the literature, although an individual patient’s prognosis cannot easily be predetermined on these features as shown in the NOB-LTS project by Briceno et al. (SNO 2021). Until now, no radiologic characteristics have been correlated with better patient outcomes. We reviewed eighteen MRI features to determine if these could aid the identification of long-term survivors (LTS).

METHODS
From the NOB-LTS cohort of our Natural History Study, 16 long-term survivals (LTS; ≥ 3 years survival post-diagnosis) were matched based on sex, age, and extent of resection to 32 control (STS, &lt; 3 years survival post-diagnosis) patients with NGS-confirmed IDH-wt glioblastoma. Pre-surgical MRIs (T1, T1 post-contrast, T2, T2/FLAIR, DWI, ADC) were reviewed by three blinded reviewers and analyzed based on pre-set criteria.

RESULTS
T1 hypointensity occurred commonly in the LTS (71%) vs STS (29%) while central heterogeneous signal occurred commonly in the STS (73%) vs LTS (50%) patients. Restricted diffusion was seen in 82% of STS and 70% of LTS cases. No difference was seen in irregular enhancement, peripheral and grey matter enhancement on T1 post-contrast images. Evaluation of T2/FLAIR images showed no difference in the number of lobes involved, presence of mass effect, heterogeneity of the signal or the perilesional signal abnormality or involvement of grey matter.

CONCLUSION
Our results suggest that pre-surgical MRI might be a useful prognostic tool as T1 hypointensity more frequently, and T1 central heterogeneity less commonly seen in the LTS group. These imaging findings may provide additional insights regarding the differences in tumor biology between LTS and STS. Further validation and correlation with histological/molecular characteristics are planned to better predict patient outcomes with newly diagnosed glioblastoma.
NCMP-01. CEREBRAL ANGIOSARCOMA AND DISTANT RADIATION THERAPY
Authors: Frontario Ariana , Bazer Danielle , Kowalska Agnieszka 
Published: November 2022

Abstract
Angiosarcoma is a rare malignant tumor originating from vascular endothelial cells. Typically, the diagnosis of angiosarcomas carry poor prognosis. Radiation exposure is one of the most common risk factors for angiosarcomas. Due to the rarity of angiosarcoma, there is sparse literature, hence it is mostly seen in case reports. We describe a case of cerebral angiosarcoma with an unknown primary malignancy in a patient with distant history of non-Hodgkin’s lymphoma treated with chemotherapy and radiation therapy to the thorax. A 54 year old male with a history of Non-Hodgkin’s Lymphoma was treated with ABVD chemotherapy and thoracic radiation therapy in 1995,presented for bilateral vision loss. Neurologic examination revealed a left homonymous hemianopia .Further investigation with brain Magnetic Resonance Imaging revealed hemorrhagic lesions in the bilateral frontal and in the right parietal-occipital lobes. Computed tomography of the chest, abdomen, and pelvis was negative for malignancy. The patient underwent a right occipital craniotomy with resection of right parietal occipital lesion. Histopathology revealed metastatic angiosarcoma. It has been acknowledged that exposure to external beam radiotherapy puts patients at risk for angiosarcoma in the future. It is believed that radiation may induce the development of AS by several mechanisms. One mechanism is the direct oncogenic effect of ionizing radiation, which can damage DNA, leading to genome instability and mutation of cancer-related genes. A prior literature review noted twenty cases of angiosarcoma developing following therapeutic irradiation. Our particular patient’s prior exposure to irridation did not include a brain radiation field, so it is unlikely this patient had radiation induced angiosarcoma.Furthermore, it does not appear that his prior radiation exposure explains the location of his angiosarcoma as his radiation field was localized to chest. Although angiosarcoma is rare, it deserves further investigation to increase the knowledge base on etiology of metastasis.
NCMP-06. VENOUS THROMBOEMBOLISM INCIDENCE AND THE IMPACT OF PRE-DISEASED ANTICOAGULATION THERAPY IN GLIOBLASTOMA PATIENTS
Authors: Sloan Anthony , Elder Theresa , Desai Ansh , Wu Anna , Choi Serah , Sloan Andrew 
Published: November 2022

Abstract
Glioblastoma (GBM) patients have a 24-30% risk of developing venous thromboembolism (VTE), including deep vein thrombosis or pulmonary embolism, over the course of their diagnosis. However, very little data exists regarding the impact of VTE on survival in GBM patients, with or without anticoagulation. This study aimed to investigate 1) the demographic factors associated with VTE incidence in GBM patients, 2) any correlation between VTE incidence and length of survival and, and 3) the impact of pre-diagnosis antiplatelet/anticoagulation therapy on VTE development and survival. A total of 150 GBM patients treated at University Hospital Seidman Cancer Center were included and retrospectively analyzed. Information was collected regarding history of aspirin, clopidogrel, DOAC, heparin, and/or warfarin use. The diagnosis of VTE both prior to GBM diagnosis and at various time points following diagnosis was determined followed by calculating overall survival and progression free survival (PFS). Of the 150 GBM patients, 53 (35.3%) developed a VTE overall. VTE incidence correlated with a lower KPS at presentation (r = -.225, p =.027) and a decrease in overall survival among GBM patients (r = -.191, p =.041). Antiplatelet/anticoagulation therapy prior to GBM diagnosis correlated with decreased VTE formation overall, as well as longer PFS among non-VTE patients (r =.261, p = .026) but not among patients who later developed VTE (r = .165, p = .302). Our findings demonstrate that patients with lower KPS are at a higher risk for developing VTE. Among GBM patients who did not develop VTEs, those on antiplatelet/anticoagulation therapy prior to diagnosis had longer PFS compared to those who were not on anticoagulants. These preliminary studies highlight the need for better VTE prophylaxis and therapy among GBM patients. These results further suggest the potential benefit of anticoagulation therapy in GBM patients irrespective of VTE formation.
NCOG-03. IMPACT OF THE RATE OF RADIOGRAPHIC RESPONSE (RR) OF BRAIN METASTASES (BM) TO WHOLE BRAIN RADIATION THERAPY (WBRT) ON NEUROCOGNITIVE FUNCTION (NCF) ON NRG-CC001
Authors: Devisetty Kiran , Pugh Stephanie , Brown Paul , Gondi Vinai , Wefel Jeffrey , Solanki Abhishek , Kalapparambath Tomy , Harmon Grant , Saripalli Anjali , Chou Brian , Venkatesulu Bhanu Prasad , Boike Thomas , Kundapur Vijayananda , Roberge David , Bovi Joseph , McGee Mackenzie , Kruser Tim , Baschnagel Andrew , Usuki Kenneth , Mehta Minesh , Kachnic Lisa 
Published: November 2022

Abstract

BACKGROUND
The assessment of BM response to WBRT and its impact on NCF in clinical trials has been limited by lack of standardized imaging protocols. NRG-CC001 is a randomized clinical trial requiring pre-specified MRI protocols at baseline and 6-months, providing a uniform dataset to investigate if RR correlates with NCF changes.

METHODS
NRG-CC001 randomized patients with BM to hippocampal avoidance WBRT (HA-WBRT) or WBRT. NCF was analyzed using 6-month standardized change scores and deterioration, defined using the reliable change index. Chi-square and t-tests were used for pretreatment characteristic comparisons. Inter-rater reliability between central and institutional assessment of RR was assessed with weighted kappa, κ. Linear regression was used to test trends in NCF change scores across types of response and multivariable logistic regression was used to test the association of RR to NCF deterioration.

RESULTS
149 and 135 patients were evaluable for RR and NCF assessment, respectively. Pretreatment characteristics were well-balanced, except for post-high school education (70.6% HA-WBRT vs. 52.5% WBRT, p=0.023). Inter-rater reliability between central and institutional assessment of RR was fair (κ=0.36). There was no difference between arms in RR (p=0.41) with overall rates of 14.1% CR, 42.2% PR, 17% SD, and 26.7% PD. Patients with CR had improved 6-month NCF change as measured by HVLT-R Total Recall (p=0.0005), HVLT-R Delayed Recall (p=0.0003), HVLT-R Delayed Recognition (p=0.011), TMT-B (p=0.033), COWA (p=0.016), and Clinical Trial Battery Composite score (p=0.0011). Multivariable analysis demonstrated less deterioration in HVLT-R Delayed Recall for CR (p=0.019) and PR (p=0.0086) vs. SD/PD and HVLT-R Recognition for PR (p=0.031) vs. SD/PD.

CONCLUSIONS
HA-WBRT and WBRT result in similar RR at 6-months. CR or PR is associated with better NCF preservation. This suggests investigation into treatment escalation for patients with SD/PD may provide further NCF benefit along with HA-WBRT and memantine.Grant support from NCI-UG1CA189867 and U24CA180803.