bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-10. A MRI-BASED RADIOMICS MODEL PREDICTING DNA DAMAGE REPAIR GENES EXPRESSION SUBTYPES AND PROGNOSIS IN GLIOBLASTOMA
Authors: Zhang Mingwei , Wu Yufan , Li Xiaoxia , Wang Xuezhen , Li Shan , Hong Jinsheng 
Published: November 2023

Abstract

BACKGROUND
Glioblastoma (GBM) is the most common primary brain tumor, with a dismal prognosis. Some DNA Damage Repair (DDR) pathways are related to progression and worse prognosis in GBM patients. However, the association between overall expression levels of DDR genes and prognosis for GBM has not been reported. Radiomics has become an essential tool for assessment of clinical information in GBM patients, expected to be a noninvasive tool for predicting DDR genes expression and prognosis.

METHODS
The TCGA database was used to obtain the GBM patients imaging, clinical and RNAseq data. We screened DDR genes and clustered them into subgroups based on their expression status, and determined differences between subgroups in prognosis and molecular mechanisms. Radiomics model based on MRI CE-T1 image was investigated to predict DDR subgroups and the output was defined as the radiomics score (RS). Prognosis analysis of RS and traditional clinical indicators was performed in TCGA cohorts, and external validated in 2 medical centers.

RESULTS
A total of 156 individuals with GBM were identified from the TCGA cohorts. 140 genes were screened in DDR gene libraries, which were classified into 2 clusters. Survival analysis showed that overall survival (OS) was significantly higher in DDR suppression subgroup than activation subgroup (21.1 vs 14.9, p=0.001), and differences in immune microenvironment, biologically active pathways were observed in the 2 groups. A model composed of 4 radiomics features were built, which can distinguish 2 DDR subgroups. RS was an independent protective factor for OS (HR=0.630, 95%CI=0.400−0.992, P=0.046). The result was externally validated by two cohorts.
NIMG-13. ROBUSTNESS OF PROGNOSTIC STRATIFICATION IN DE NOVO GLIOBLASTOMA PATIENTS ACROSS 22 GEOGRAPHICALLY DISTINCT INSTITUTIONS: INSIGHTS FROM THE RESPOND CONSORTIUM
Authors: Akbari Hamed , Bakas Spyridon , Garcia Jose , Kazerooni Anahita Fathi , Sako Chiharu , Villanueva-Meyer Javier , Baid Ujjwal , Mamourian Elizabeth , Brem Steven , Lustig Robert A , Nasrallah MacLean P , O'Rourke Donald M , Calabrese Evan , Rudie Jeffrey , Chang Susan , Rauschecker Andreas , LaMontagne Pamela , Marcus Daniel S , Balana Carmen , Capellades Jaume , Puig Josep , Barnholtz-Sloan Jill , Badve Chaitra , Sloan Andrew , Waite Kristin , Colen Rivka , Choi Yoon Seong , Ahn Sung Soo , Dicker Adam P , Flanders Adam E , Shi Wenyin , Griffith Brent , Poisson Laila M , Rogers Lisa R , Booth Thomas C , Jain Rajan , Chakravarti Arnab , Palmer Joshua , Cepeda Santiago , Wiestler Benedikt , Stefano Anna Luisa Di , Alexander Kimberley , Melhem Elias R , Woodworth Graeme F , Kamel Peter I , Tiwari Pallavi , Aboian Mariam , Mohan Suyash , Davatzikos Christos 
Published: November 2023

Abstract

PURPOSE
Glioblastoma is the most prevalent primary malignant brain tumor in adults, with a median overall survival (OS) of approximately 15 months and only limited advancements in prognostication and survival prediction. This study aims to evaluate an AI-based prognostic stratification model for OS prediction trained on the ReSPOND consortium data and to validate its performance on an independent dataset.

METHODS
The AI model was trained on a cohort of 2,293 glioblastoma patients from 22 institutions across three continents. For validation, an independent cohort of 78 treatment-naïve patients was used from three institutions. Preoperative structural MRI scans were utilized for feature extraction. Automated segmentation defined three tumor sub-compartments: enhancing, necrotic, and peritumoral T2-FLAIR abnormality. The AI predictor incorporated variables such as patient age, normalized tumor sub-compartment volume, spatial distribution characteristics, and morphologic descriptors. The overall survival predictor index provided a continuous value between 0 and 1 for patient stratification that higher values indicating longer predicted OS. Generalizability was assessed using Leave-One-Cohort-Out-Cross-Validation (LOCOCV) for training data, and the model was subsequently applied to the validation cohort.

RESULTS
Survival analysis demonstrated a concordance index of 0.64 for LOCOCV training data and 0.59 for the independent validation data, indicating effective prognostic stratification of patients.

CONCLUSION
Multi-parametric AI assisted image analysis extracts prognostic biomarkers, which correlate with OS in glioblastoma patients. The generalizability of this method was validated using the extensive centralized glioblastoma imaging dataset registry from the ReSPOND consortium and an independent dataset, demonstrating its generalizability across diverse patient populations and acquisition settings. This model holds promise for robust prognostic stratification and prediction in de novo glioblastoma patients.
NIMG-19. TUMOR PARAMETERS AFFECTED BY NANOCOMBRESTATIN THERAPY IN AN EXPERIMENTAL RAT MODEL OF GLIOMA
Authors: Ali Meser , deCarvalho Ana , Ewing James , Snyder James , Mikkelsen Tom 
Published: November 2023

Abstract
INTRODUCTION: of polymeric nanoparticles in cancer therapeutics is widely investigated since nanomedicine often enables the intratumoral delivery of drugs with increased efficacy with minimal side effects. In this study magnetic resonance imaging (MRI) monitoring was employed to study the therapeutic effect of nanocombretastatin (G3-CA4) in an orthotopic glioma model. Water insoluble combretastatin (CA4) was conjugated to a small-sized water soluble G3-succinimic acid PAMAM dendrimer. Tumor growth and vascular parameters were assessed non-invasively using MRI. In the brain, intravenously (iv) administered magnetic resonance (MR) contrast agents (CAs) can be used to measure the biomarkers of tumor perfusion - the blood-to-brain transvascular transfer constant (K-trans), tumor plasma volume (Vp), the extravascular extracellular space (Ve) and the blood volume (VD) in cerebral tumors. K-trans, Vp, Ve and VD showed the discrimination of tumorous vasculature responding to CA4 and G3-CA4 therapies from tumorous tissues. The average K-trans, Vp, Ve and VD decreased significantly 24 hours after G3-CA4 treatment. The results showed that G3-CA4 caused a change in tumor vasculature as measured with DCE-MRI. These effects were homogenous throughout the U-251 tumor. However, CA4 did not show any change in tumor vasculature. Imaging, histological and molecular signatures of the primary glioblastoma were compared. Large necrotic area was found together with destroyed blood vessels at the core of the tumor leaving viable tissue at the rim of the tumor. In vivo studies proved that the cytotoxicity of G3-CA4 conjugate was more effective against human U-251 tumor while CA4 alone was ineffective. Therefore, we have accomplished the effective transvascular delivery of G3-CA4 into human U251 glioma tumor with a compromised blood brain tumor barrier. In vivo studies proved that the cytotoxicity of G3-CA4 conjugate is more effective against human U-251 tumor than that of free CA4.
NIMG-24. RECURRENT OLIGODENDROGLIOMA DEMONSTRATES EARLY INCREASE IN CEREBRAL BLOOD FLOW AND NORMALIZATION IN RESPONSE TO TREATMENT
Authors: Oztek Alp , Andre Jalal , McGranahan Tresa 
Published: November 2023

Abstract
Oligodendrogliomas, molecularly defined by the presence of both IDH mutation and 1p/19q codeletion, are more treatment responsive than other gliomas, and due to short capillary segments, demonstrate elevated CBF regardless of grade or contrast enhancement. Arterial Spin Labeling (ASL) allows noninvasive perfusion imaging assessment of cerebral blood flow (CBF) without contrast administration. Changes in CBF are recognized in association with malignant transformation of gliomas however in the setting of treatment, CBF has only been studied to assist in differentiating radiation treatment effect from progressive glioma. This single center retrospective study was undertaken to evaluate if CBF, measured by ASL, might normalize following treatment of recurrent oligodendrogliomas. Clinical database query identified 151 patients with molecularly confirmed oligodendroglioma, 34 of which had available ASL imaging. Expert reader review of all available MRI sequences, blinded to treatment timeline, were performed by two independent radiologists at a PACS station. There were 6 radiographic recurrences identified and in 5/6 CBF was the first radiographic change. Contrast enhancement did not develop for 1.5-12 months after change in CBF for 4/5 recurrences. ASL imaging before and after non-surgical therapy for recurrent disease was available for 4 patients. Two patients were treated with lomustine, one with bevacizumab and one with proton re-radiation. By the second MRI following treatment initiation, all patients had normalization of CBF. At the first post treatment MRI, 3/4 of patients demonstrated normalization of CBF while only 2/4 demonstrated normalization of dynamic susceptibility contrast-derived cerebral blood volume. During the subsequent 6 months, FLAIR hyperintensities remained stable in all patients. This work supports further study if normalization of ASL-derived CBF may be an early radiographic biomarker for response to treatment, especially in non or minimally enhancing recurrent gliomas.
NIMG-31. AXONS INTERSECTING TUMOR ENHANCEMENT (AXITE) RADIOMICS: A NOVEL PREDICTOR FOR OVERALL SURVIVAL IN GLIOBLASTOMA
Authors: Nath Biprojit , Winiarz Aleksandra , Bobholz Samuel , Lowman Allison , Duenweg Savannah , Stebbins Margaret , Flatley Michael , Kyereme Fitzgerald , Connelly Jennifer , Coss Dylan , Krucoff Max , Banerjee Anjishnu , LaViolette Peter 
Published: November 2023

Abstract

AIM
The diffuse infiltration of glioblastoma (GBM) along the intricate network of white matter (WM) tracts poses a major challenge. Our aim is to investigate the potential of axons intersecting tumor enhancement (AXITE)-derived radiomic features in predicting one-year overall survival (OS), in comparison to conventional tumor-based radiomics.

METHODS
This study included data from the publicly available UCSF-PDGM-v2 (n=97). T1+C images and their corresponding tumor mask were rigidly registered to a common brain template (MNI152) using ANTs. WM tracts within the tumor-defined region of interest were generated using the HCP1065-1mm tractography atlas in DSI Studio Software, which mapped the AXITEs. Radiomic features were then extracted using PyRadiomics from subsequently masked AXITE maps as well as contrast-enhancing tumor masks for a comparative analysis. Four machine learning models, including a Random Forest, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, were employed to predict OS using an 80/20 train/test split.

RESULTS
Among all models, SVM was the most effective in predicting OS. AXITE radiomics demonstrated remarkable precision (0.73 for OS &lt; 1 yr and 0.78 for OS &gt;1yr), accuracy (0.75), F1-Score (0.75), recall (0.75), and AUC of 0.84 in ROC analysis outclassing the performance of traditional tumor radiomics which had an accuracy (0.60), precision (0.66), F1-Score (0.56) and AUC of 0.60.

CONCLUSIONS
AXITE Radiomics holds promising potential in capturing tumoral heterogeneity and white matter tract infiltration of GBM, demonstrating superior prediction over traditional tumor radiomics. Our approach presents a more accurate representation of tumor invasiveness and tumor resistance associated with OS more accurately and promises a potential tool for improving patient prognosis and patient management.
NIMG-33. [18F]-FLUOROMISONIDAZOLE RELATIVE PET INFLUX RATE IMPROVES DIAGNOSTIC ACCURACY FOR GLIOBLASTOMA PROGRESSION FROM THERAPY-INDUCED NEUROINFLAMMATORY PSEUDOPROGRESSION
Authors: Wishart Joseph , Barajas Ramon , Pugachev Andrei , Winters Celeste , Nemeh Sadek , Ivanidze Jana , Link Jeanne , Ambady Prakash 
Published: November 2023

Abstract
Glioblastoma is the most common and aggressive form of primary brain tumor in adults. Standard of care gadolinium-enhanced MRI (Gd-MRI) fails to capture hypoxia, a disease-defining feature of glioblastoma. Hypoxia potentiates resistance to chemo-radiation therapy (CRT) but is not extensively observed with therapy-induced pseudoprogression (PSP). This neuroinflammatory response to CRT occurs in approximately 40% of patients and is indistinguishable from disease progression by Gd-MRI, potentially causing unnecessary termination of effective therapy in patients with PSP. Additionally, delayed second line-therapy can occur in patients with resistance to CRT. This research evaluated whether [18F]-fluoromisonidazole (FMISO) positron emission tomography (PET), a noninvasive metric of tissue hypoxia, improves diagnostic accuracy in this context. Clinically, PET quantification employs the standardized uptake value (SUV), representing summed counts over an acquisition period. To add accuracy to this assessment, static 40-minute PET data acquired starting 90 minutes after FMISO injection was reconstructed into 20x2-minute frames and a relative Patlak model was applied. This technique forgoes blood sampling and extensive examination times required by traditional dynamic PET studies. The model produces two parameters that separately characterize the FMISO relative influx rate (Ki') and blood volume (VB'). In a cohort of 16 patients (3 IDH-mutated) imaged at a time of presumed disease progression, results showed that Ki' within the Gd-MRI enhancing lesion predicts future diagnosis of true progression (n = 11) or inflammation (n =5 ) with a sensitivity and specificity of 91% and 80% respectively. This outperforms diagnosis made with Gd-MRI alone, achieving ~70% for the same metrics. A t-test assuming unequal variance of cohort-wide mean Ki' tended toward significance (p = 0.07) for differentiating progressive disease (0.0036 ± 0.0016 min-1) from PSP (0.0011 ± 0.0017 min-1). RESULTS: from this study suggest relative Patlak analysis adds specificity to Gd-MRI and provides clinically relevant information regarding disease status.
NIMG-34. TEMPORAL MUSCLE THICKNESS AS A PROGNOSTIC MARKER IN A REAL-LIFE COHORT OF NEWLY DIAGNOSED MGMT PROMOTER METHYLATED GLIOBLASTOMA PATIENTS: A MULTICENTRIC IMAGING ANALYSIS
Authors: Lazaridis Lazaros , Moenninghoff Christoph , Bumes Elisabeth , Spille Dorothee Cäcilia , Müther Michael , Schulz Tim , Heider Sina , Agkatsev Sarina , Schmidt Teresa , Blau Tobias , Oster Christoph , Stummer Walter , Kessler Almuth Friederike , Seidel Clemens , Grauer Oliver , Hau Peter , Sure Ulrich , Keyvani Kathy , Herrlinger Ulrich , Kleinschnitz Christoph , Stuschke Martin , Herrmann Ken , Deuschl Cornelius , Scheffler Björn , Kebir Sied , Glas Martin 
Published: November 2023

Abstract

BACKGROUND
In cranial MRI assessed temporal muscle thickness (TMT) correlates with lumbar skeletal muscle mass, which serves as surrogate marker of sarcopenia. Prior research has identified TMT as a prognostic marker in glioblastoma. However, incorporation into clinical practice is challenging due to the heterogeneity of previous studies and the absence of established cutoff values. To address this, we conducted a multicenter analysis to validate recently proposed sex-specific cutoff values in a homogeneous real-life cohort of newly diagnosed MGMT promoter-methylated glioblastoma patients uniformly treated with combined CCNU/temozolomide. We implemented a balanced control cohort for comparison.

METHODS
TMT was measured at baseline using preoperative or early postoperative MRI and in the disease course using the first MRI after completion of radiotherapy. Patients were TMT-based divided into “at risk of sarcopenia” or “normal muscle status”. Kaplan-Meier statistics and multivariable Cox regression analysis were used for correlation with survival.

RESULTS
In total, n = 126 patients were analyzed (n = 66 received CCNU/temozolomide; n = 60 received temozolomide). Patients with normal muscle mass at baseline (&gt; 6,3 mm for men; &gt; 5,2 mm for women) had significantly prolonged mOS (44.3 versus 16.7 months for CCNU/temozolomide; 29.5 versus 17.4 months for temozolomide) compared to those at risk of sarcopenia. In a multivariable Cox regression analysis, normal muscle mass (HR: 0.39, 95% CI: 0.23-0.66; p = 0.0003) and age at diagnosis of &lt; 50 years (HR: 0.42, 95% CI: 0.22-0.79; p = 0.0067) were significant prognostic markers. Longitudinally, survival was best in patients with lack of TMT decline.

CONCLUSIONS
This analysis suggests TMT to serve as a prognostic marker in glioblastoma patients treated with CCNU/temozolomide or with temozolomide. However, for TMT assessment to be implemented in a generalizable manner, such as for patient selection for therapeutic measures, further validation in prospective controlled trials is necessary.
NIMG-36. IMAGE LOCALIZATION OF CLINICAL SAMPLES IN BRAIN CANCER: A PROSPECTIVE PROTOCOL
Authors: Langworthy Jazlynn , Curtin Lee , Spahiu Albana , Schafer Nora , Bendok Bernard , Baxter Leslie , Hu Leland , Zimmerman Richard , Swanson Kristin 
Published: November 2023

Abstract
It has been widely acknowledged that limited access to the human brain, along with the importance of its structures, presents significant challenges in obtaining brain tumor tissue. This poses difficulties for clinical decision-making, as healthcare professionals often have to rely solely on imaging to address complex problems. There is currently no definitive method to make these decisions other than relying on informed yet subjective human judgment. That said, imaging abnormalities are a result of a presence of particular tumor-related biology. Because of this, and the heterogeneity frequently observed in brain tumors, we have developed an image-localized biopsy protocol that has been employed for research purposes at Mayo Clinic Arizona for over five years. This multidisciplinary approach involves the collaborative efforts from neurosurgeons, neuro-oncologists, scrub-techs, nurses, radiologists, as well as multiple research labs, all working within a well-established pipeline. The implementation of this protocol has allowed us to obtain image-localized biopsies during surgical procedures, enabling the correlation of local imaging findings with corresponding tissue features through the utilization of machine learning models. The primary objective of this endeavor is to enhance our understanding of the underlying biological mechanisms of brain tumors based on patients' imaging data. This protocol has been successful for our research purposes, and with minor adjustments, it can be readily adopted by any hospital in order to collect more data about these incredibly heterogeneous diseases. While the use of neuronavigation during surgery has become commonplace in many medical institutions, localization of tissue samples is not. Utilizing pre-existing infrastructure in the operating room is a small burden with big potential positive outcomes. Sample locations can be useful to clinicians during tumor board discussions, to better assess disease heterogeneity. These minor refinements in the surgical workflow have the capacity to provide clinicians with additional clinically-relevant data without disrupting patient care.
NIMG-38. TUMOR VOLUME GROWTH RATES AND DOUBLING TIMES DURING ACTIVE SURVEILLANCE OF IDH-MUTANT LOW-GRADE GLIOMA
Authors: Bhatia Ankush , Moreno Raquel , Reiner Anne , Nandakumar Subhiksha , Walch Henry , Thomas Teena , Nicklin Philip , Choi Clara , Skakodub Anna , Malani Rachna , Prabhakaran Vivek , Tiwari Pallavi , Diaz Maria , Panageas Katherine , Mellinghoff Ingo , Bale Tejus , Young Robert 
Published: November 2023

Abstract

PURPOSE
Isocitrate-dehydrogenase-mutant (IDH-mt) gliomas are incurable primary brain tumors characterized by a slow-growing phase over several years followed by a rapid-growing malignant phase. We hypothesized that tumor volume growth rate (TVGR) on magnetic resonance imaging may act as an earlier measure of clinical benefit during the active surveillance period.

METHODS
We integrated 3-dimensional volumetric measurements with clinical, radiological, and molecular data in a retrospective cohort of IDH-mt gliomas that were observed after surgical resection in order to understand tumor growth kinetics and the impact of molecular genetics.

RESULTS
Using log-linear mixed modeling, the entire cohort (n=128) had a continuous %TVGR per 6 months of 10.46% (95% CI: [9.11%, 11.83%]) and a doubling time of 3.5 years (95% CI: [3.10-3.98]). High molecular grade IDH-mt gliomas, defined by the presence of homozygous deletion of CDKN2A/B, had %TVGR per 6 months of 19.17% (95% CI: [15.57%, 22.89%]) which was significantly different from low molecular grade IDH-mt gliomas with a growth rate per 6 months of 9.54% (95% CI: [7.32%, 11.80%]) (P &lt; 0.0001). Using joint modeling to co-model the longitudinal course of TVGR and overall survival, we found each unit increase in log volume resulted in more than a 3-fold increase in risk of death (HR=3.83, 95% CI: [2.32-6.30], P &lt; 0.0001).

CONCLUSIONS
TVGR may be used as an earlier measure of clinical benefit and correlates well with the WHO 2021 molecular classification of gliomas and survival. Incorporation of TVGR as a surrogate endpoint into future prospective studies of IDH-mt gliomas may accelerate drug development.
NIMG-40. SUPER T2-FLAIR MISMATCH SIGN AS PROGNOSTIC IMAGING BIOMARKER FOR NON-ENHANCED ASTROCYTOMA, IDH-MUTANT
Authors: Ozono Iori , Onishi Shumpei , Takayasu Takeshi , Yonezawa Ushio , Taguchi Akira , Khairunissa Novita , Yamasaki Fumiyuki , Horie Nobutaka 
Published: November 2023

Abstract

BACKGROUND
The T2-FLAIR mismatch sign has been established as a highly specific diagnostic imaging biomarker for astrocytoma, IDH-mutant. However, prognostic imaging biomarker for this tumor has not been well established.

METHODS
We retrospectively reviewed 31 cases of non-enhanced astrocytoma, IDH-mutant, WHO grade 2 and 3 treated at our hospital. We defined “super T2-FLAIR mismatch sign” positivity as having a significantly strong low signal comparable to cerebrospinal fluid, rather than just a pale FLAIR low-signal tumor region as in regular T2-FLAIR mismatch. We evaluated the presence or absence of T2-FLAIR mismatch sign and super T2-FLAIR mismatch sign using preoperative MRI and statistically analyzed the progression-free survival (PFS) and overall survival (OS) using log-rank test.

RESULTS
The median age of this patient group was 40 (ranging 19-75) years, and consisted with 21 males and 10 females., with 21 males and 10 females. There were 25 cases of grade 2 and six cases of grade 3. T2-FLAIR mismatch sign was observed in 17 cases (54.8%) (grade 2: 16 cases, grade 3: 1 case), and super T2-FLAIR mismatch sign was observed in eight cases (25.8%) (grade 2: 8 cases). The presence or absence of T2-FLAIR mismatch sign was not associated with both PFS (46.8 months vs. 33.6 months, p=0.2526) and OS (not reached vs. 152 months, p=0.2087). Positive super T2-FLAIR mismatch sign cases have propensity to show longer PFS (112.7 months vs. 36.0 months, p=0.0710), and significantly longer OS (not reached vs. 152 months, p=0.0392). When super T2-FLAIR mismatch sign-positive cases were compared to negative cases in patients who did not accomplish entire removal, the PFS was significantly longer (p=0.0045) and there was a propensity for a longer OS (p=0.0543).

CONCLUSIONS
Super T2-FLAIR mismatch sign can be considered as a prognostic imaging biomarker for non-enhanced astrocytoma, IDH-mutant.