bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIMG-26. UPTAKE OF [18F]GE-180 IN TSPO PET IS ASSOCIATED WITH SURVIVAL IN PATIENTS WITH RECURRENT GLIOMA
Authors: Quach Stefanie , Holzgreve Adrien , Kaiser Lena , Unterrainer Marcus , Dekorsy Franziska , Nelwan Debie V , Bartos Laura , Kirchleitner Sabrina , Weller Jonathan , Weidner Lorraine , Niyazi Maximilian , Ruf Victoria , Herms Jochen , Stöcklein Sophia , Wetzel Christian , Riemenschneider Markus J , von Baumgarten Louisa , Thon Niklas , Brendel Matthias , Rupprecht Rainer , Bartenstein Peter , Tonn Joerg-Christian , Albert Nathalie 
Published: November 2022

Abstract

OBJECTIVE
The 18 kDa translocator protein (TSPO) is expressed in both activated microglia and glioma cells. Elevated expression of TSPO has been reported to be associated with higher WHO grade. Here we analyze whether TSPO positron emission tomography (PET) signal using the tracer [18F]GE-180 is correlated with clinical outcome in a cohort of patients with recurrent glioma.

METHODS
Patients with suspected glioma recurrence received a [18F]GE-180 TSPO PET. All recurrent tumors were confirmed either by stereotactic biopsy or resection. Maximum standard uptake value SUVmax as well as tumor volume in MRI and, if available, in [18F]FET PET were evaluated together with patient characteristics (age, sex, Karnofsky-Performance score) and neuropathological features (WHO grade, IDH-mutation status). Uni- and multivariate Cox regression and Kaplan-Meier survival analyses were performed to identify prognostic factors for post-recurrence survival (PRS) and time to treatment failure (TTF).

RESULTS
88 consecutive patients were evaluated. TSPO tracer uptake correlated with tumor grade at recurrence (p&lt; 0.05), with no significant differences between IDH-wildtype and IDH-mutant tumors. Within the subgroup of IDH-mutant glioma (n= 46), patients with low SUVmax (median split, ≤ 1.60) had a significantly longer PRS (median 41.6 vs. 25.3 months, p= 0.031) and TTF (32.2 vs 8.7 months, p= 0.001). Also among IDH-wildtype tumors (n= 42), patients with low SUVmax (≤ 1.89) had a significantly longer PRS (median not reached vs 8.2 months, p= 0.002). SUVmax remained an independent prognostic factor for PRS in a multivariate analysis including WHO grade, IDH status and age. Tumor volume defined by [18F]FET PET or contrast-enhanced MRI correlated weakly with TSPO tracer uptake. Treatment regimen did not differ between the subgroups.

CONCLUSION
Our data suggest that uptake of [18F]GE-180 in TSPO PET can add prognostic information in patients with recurrent glioma even in molecular defined subgroups and might serve as an imaging biomarker.
NIMG-27. THE PROGNOSTIC VALUE OF FET PET IN PATIENTS WITH RECURRENT GLIOMA TREATED WITH BEVACIZUMAB
Authors: Werner Jan-Michael , Winkels Myriam , Lohmann Philipp , Ceccon Garry , Wollring Michael , Tscherpel Caroline , Bauer Elena , Goldbrunner Roland , Stoffels Gabriele , Langen Karl-Josef , Fink Gereon R , Galldiks Norbert 
Published: November 2022

Abstract

BACKGROUND
After multiple recurrences in glioma patients, bevacizumab is frequently used as salvage therapy. In this group of patients, we evaluated the prognostic value of amino acid PET using O-(2-[18F]fluoroethyl)-L-tyrosine (FET) before initiation of bevacizumab.

METHODS
We retrospectively identified adult glioma patients at recurrence with (i) at least one or more previous recurrences, (ii) who were treated with bevacizumab, and (iii) who underwent FET PET imaging before bevacizumab initiation. Maximum and mean tumor-to-brain ratios (TBRmax, TBRmean), metabolic tumor volume (MTV), and dynamic parameters (i.e., time-to-peak, slope) were obtained from FET PET. Additionally, contrast-enhancing volumes on MRI were calculated. Threshold values of imaging parameters for evaluating the prognosis were established by ROC analyses using overall survival (OS) of ≥ 6 months as reference. The prognostic value of imaging parameters was subsequently evaluated using the log-rank test and multiple logistic regression analyses.

RESULTS
Twenty-eight patients (glioblastoma, 96%) with a median of 2 recurrences (range, 1-5) were eligible for data evaluation. The patients received a median number of 7 bevacizumab cycles (range, 1-27). The static FET PET parameter TBRmean was the best parameter (threshold, 2.1; AUC, 0.78; P=0.014) to identify patients with a significantly longer OS (8.2 vs. 4.9 months; P=0.044). In contrast, the MTV, contrast-enhancing volume, and dynamic FET PET parameters were not significant. TBRmean remained significant in multiple logistic regression analysis (P=0.031), indicating an independent predictor for OS.

CONCLUSION
Our data suggest that static FET PET allows identifying patients with longer OS before initiation of bevacizumab.
NIMG-29. ASSOCIATION OF PARTIAL T2-FLAIR MISMATCH SIGN AND ISOCITRATE DEHYDROGENASE MUTATION IN WHO GRADE 4 GLIOMA/GLIOBLASTOMA: RESULTS FROM THE RESPOND CONSORTIUM
Authors: Lee Matthew , Sako Chiharu , Patel Sohil , Mohan Suyash , Balana Carmen , Barnholtz-Sloan Jill , Sloan Andrew , Badve Chaitra , Poisson Laila , Griffith Brent , Booth Thomas , Palmer Joshua , Chakravarti Arnab , Bakas Spyridon , Nasrallah MacLean , Choi Yoon Seong , Dicker Adam , Flanders Adam , Shi Wenyin , Mahajan Abhishek , Colen Rivka , Marcus Daniel , Orringer Daniel , Davatzikos Christos , Jain Rajan 
Published: November 2022

Abstract

PURPOSE
T2-FLAIR mismatch (T2FM) is a highly specific imaging biomarker for isocitrate dehydrogenase (IDH) mutation in low-grade gliomas. Previous T2FM studies are inconsistent for glioblastoma (GBM)/grade-4 glioma, partly due to low IDH-mutation prevalence in high-grade gliomas. We leveraged a large multi-institutional GBM/grade-4 glioma cohort to analyze the association of partial T2FM and IDH-mutation (T2-hyperintense, FLAIR-hypointense, nonenhancing, nonedema).

METHODS
We analyzed preoperative MRI of 1500 pathologically confirmed GBM/grade-4 gliomas with known IDH-mutation status from the ReSPOND consortium, consisting of the following institutions (sample size): Ivy GBM Atlas Project (33), Catalan Institute of Oncology (132), Case Western Reserve University/University Hospitals (132), New York University (55), Ohio State University (25), University of Pennsylvania (641), University Hospital Río Hortega (16), Yonsei University Health System (118), The Cancer Imaging Archive (93), Thomas Jefferson University (48), Tata Memorial Hospital (22), University of Pittsburgh Medical Center (156), and Washington University School of Medicine in St. Louis (57). Sequences were co-registered to a common anatomic atlas. Continuous variables were compared by t-test and categorical variables by Χ 2-test.

RESULTS
71 (4.7%) were IDH-mutants, significantly younger (43±1 v. 62±12 years, p=5x10-37), and more likely to exhibit partial T2FM (20% v. 0.4%, p=1x10-43), frontal lobe predominance (68% v. 29%, p=7x10-12), nonenhancing components (T2/FLAIR-intermediate signal, nonedema; 45% v. 9%, p=1x10-22), and cystic components (smooth margins, no/minimal enhancement, homogeneous FLAIR suppression; 17% v. 3%, p=7x10-11) than IDH-wildtypes. 20 cases had partial T2FM (14 IDH-mutant, 6 IDH-wildtype). Sensitivity of partial T2FM for IDH-mutation was 19.7%, specificity 99.6%, positive predictive value 70%, and negative predictive value 96.1%. Subset analysis of 983 IDH-wildtypes with known MGMT methylation status (406 MGMT-hypermethylated) showed frontal lobe predominance was more common in MGMT-hypermethylated than MGMT-unmethylated (39.4% v. 24.3%, p=.02); other imaging characteristics did not significantly differ.

CONCLUSIONS
Partial T2FM is a highly specific imaging biomarker for IDH-mutation in GBM/grade-4 glioma.
NIMG-30. AI-BASED MOLECULAR CLASSIFICATION OF DIFFUSE GLIOMAS USING RAPID, LABEL-FREE OPTICAL HISTOLOGY
Authors: Hollon Todd , Jiang Cheng , Nasir-Moin Mustafa , Kondepudi Akhil , Chowdury Asadur , Al-Holou Wajd , Castro Maria , Lowenstein Pedro , Wadiura Lisa Irina , Widhalm Georg , Neuschmelting Volker , David Reinecke , von Spreckelsen Niklas , Berger Mitchel S , Golfinos John , Hervey-Jumper Shawn L , Camelo-Piragua Sandra , Lee Honglak , Freudiger Christian , Orringer Daniel 
Published: November 2022

Abstract

INTRODUCTION
Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. Access to timely molecular diagnostic testing for brain tumor patients is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment.

OBJECTIVE
We aim to develop a rapid (&lt; 90 seconds), AI-based diagnostic screening system that can provide molecular classification of diffuse gliomas and report its use in a prospective, multicenter, international clinical trial of diffuse glioma patients (n = 153).

METHODS
By combining stimulated Raman histology (SRH), a rapid, label-free, non-consumptive, optical imaging method, and deep learning-based image classification, we are able to predict the molecular genetic features used by the World Health Organization (WHO) to define the adult-type diffuse glioma taxonomy, including IDH-1/2, 1p19q-codeletion, and ATRX loss. We developed a multimodal deep neural network training strategy that uses both SRH images and large-scale, public diffuse glioma genomic data in order to achieve optimal molecular classification performance.

RESULTS
One institution was used for model training (University of Michigan) and four institutions (NYU, UCSF, Medical University of Vienna, and University Hospital Cologne) were included for prospective patient enrollment and model testing. Using our system, called DeepGlioma, we achieved an average molecular genetic classification accuracy of 93.2% and identified the correct diffuse glioma molecular subgroup with 91.5% accuracy. DeepGlioma outperformed conventional IDH1-R132H immunohistochemistry (94.2% versus 91.4% accuracy, respectively) as a first-line molecular diagnostic screening method for diffuse gliomas, detecting canonical and non-canonical IDH mutations with high accuracy.

CONCLUSION
Our results demonstrate how artificial intelligence and optical histology can be used to provide a rapid and scalable alternative to wet lab methods for the molecular diagnosis of brain tumor patients during surgery.
NIMG-39. AMINO ACID PET-MRI OF HIGH-GRADE GLIOMA
Authors: Harat Maciej , Rakowska Józefina , Harat Marek , Szylberg Tadeusz , Furtak Jacek , Miechowicz Izabela , Małkowski Bogdan 
Published: November 2022

Abstract

OBJECTIVE
MRI is gold standard for the diagnosis, surgery and radiation therapy of patients with high-grade glioma. Amino acid PET is useful in gliomas without contrast enhancement in MRI but it is unknown whether PET better identifies high-grade foci than T1-sequence with contrast enhancement or improve definition of high grade glioma infiltration related to T2/Flair images.

METHODS
More than 400 biopsy specimens from twenty-three patients with suspected high-grade glioma were examined in this prospective study. Patients meeting the inclusion criteria were referred for hybrid 18F-FET-PET-MRI before stereotactic biopsy. Biopsies were planned based on early FET-PET acquisition 5-15 minutes post injection and MRI. The following biopsy sites were determined in each case: (i) site of contrast enhancement and increased FET uptake; (ii) contrast enhancement but no increase in FET uptake; (iii) increased FET uptake but without contrast enhancement; and (iv) peripheral areas hyperintense in T2 FLAIR without increased FET uptake and contrast enhancement.

RESULTS
In 35% cases, the biopsy result was changed to a higher tumor grade after the inclusion of FET-positive sites. In all cases, high FET uptake was visualized and confirmed outside areas of contrast enhancement on MRI, indicative of high-grade glioma. Results from biopsies based on the FLAIR sequences corresponded to neoplastic lesions in 13 cases (57%), most often with a lower grade than in areas of high FET uptake.

CONCLUSIONS
FET-PET can be used to locate the most malignant areas of contrast-enhancing gliomas and impact the biopsy results. Surgery or radiotherapy planned solely on MRI images may miss parts of tumor presenting highest malignancy. Brain areas hyperintense in T2 FLAIR without increased amino acid uptake are not specific for malignancy in high grade gliomas.
NIMG-43. DIFFUSION BASIS SPECTRUM IMAGING DISTINGUISHES HIGH-GRADE GLIOMA TREATMENT EFFECT FROM TUMOR PROGRESSION
Authors: Han Rowland , Johanns Tanner , Blum Jacob , Ye Zezhong , Sun Peng , Lin Tsen-Hsuan , Kim Albert , Song Sheng-Kwei 
Published: November 2022

Abstract

BACKGROUND
Following standard-of-care chemoradiation therapy for high-grade glioma, it is often challenging to distinguish treatment changes from true tumor progression using conventional magnetic resonance imaging (MRI). Diffusion basis spectrum imaging (DBSI) uses a data-driven multiple-tensor modeling approach to disentangle specific histologic components and structural features present within individual imaging voxels, offering an opportunity to noninvasively differentiate treatment effect from tumor progression. This represents the first study of in vivo longitudinal DBSI for brain tumors in patients.

METHODS
Adult patients were prospectively recruited who met the criteria of known pathological diagnosis of high-grade glioma or glioblastoma (WHO grade III-IV) and undergoing or completing standard-of-care radiation therapy with concurrent chemotherapy. DBSI and conventional MRI data were acquired longitudinally beginning with a 4-week post-radiation therapy MRI until progression as defined by standard RANO criteria or biopsy. DBSI analyses were performed with isotropic diffusion profiles defined as restricted fraction (0 ≤ D ≤ 1.0 μm2/ms) and hindered fraction (1.0 &lt; D ≤ 1.5 μm2/ms).

RESULTS
Eleven patients with contrast-enhancing high-grade gliomas were enrolled between June 2019 and March 2020, with final DBSI data obtained in November 2020. Of these, eight patients had tumor progression, two had treatment effect, and one had stable disease during the study period. Within the contrast-enhancing regions, the DBSI hindered fraction map demonstrated hypointensity for all cases of tumor progression, and hyperintensity for cases of treatment effect. DBSI-based biomarkers were present 0.7 to 12.0 months (median 2.4, IQR 2.8) before definitive diagnosis of treatment effect or tumor progression using conventional methods of MRI and/or biopsy.

CONCLUSIONS
DBSI hindered fraction can distinguish new contrast-enhancing lesions in the setting of high-grade glioma as treatment effect or tumor progression in advance of conventional MRI. Future work will incorporate machine learning algorithms to further improve DBSI-based predictions of tumor histopathology.
NIMG-45. DISTINGUISHING PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMA: COMBINED USE OF 18F-FLUCICLOVINE PET AND MULTI-PARAMETRIC MRI
Authors: Nabavizadeh Ali , Bagley Stephen , Ware Jeffrey B , Doot Robert K , Young Anthony , Ghodasara Satyam , Zhao Chao , Anderson Hannah , Schubert Erin , Carpenter Erica L , Till Jacob , Henderson Fraser , Pantel Austin R , Chen Isaac , Lee John Y K , Amankulor Nduka , O'Rourke Donald , Desai Arati , Nasrallah MacLean , Brem Steven 
Published: November 2022

Abstract

PURPOSE
Differentiation of tumor progression (TP) from pseudoprogression (PsP) is a major unmet need in post-treatment glioblastoma (GBM). 18F-Fluciclovine is a synthetic amino acid PET radiotracer with higher uptake in tumor tissue vs. areas of treatment-related change. We investigated the value of 18F-Fluciclovine PET for differentiating PsP from TP independent from and in combination with multi-parametric MRI.

METHODS
We prospectively enrolled 30 patients with GBM with a new or enlarging contrast-enhancing lesion on MRI after chemoradiotherapy who were planned for surgical resection of the lesion. Patients underwent pre-operative 18F-Fluciclovine PET and multi-parametric MRI. Following surgery, the relative percentages of viable tumor and therapy-related changes observed in histopathology were quantified. Patients were categorized as TP if viable tumor represented ≥ 50% of the specimen, mixed TP if &lt; 50% and &gt; 10%, and PsP if ≤ 10%.

RESULTS
18 patients had TP, 4 had mixed TP, and 8 PsP. Patients with TP/mixed TP had a significantly higher 40-50 minutes SUVmax (6.64 + 1.88 vs 4.11± 1.52, p=0.009) and an SUVmax cut-off of 4.66 provided 90% sensitivity and 83% specificity for differentiation of TP/mixed TP from PsP (AUC=0.856). A maximum cerebral blood volume (CBVmax) cut-off of 3.67 provided 90% sensitivity and 71% specificity for differentiation of TP/mixed TP from PsP (AUC=0.779). Combining a 40-50 minutes SUVmax cut-off of 4.662 and a relative CBVmax cut-off of 3.67 provided 100% sensitivity and 80% specificity for differentiating TP/mixed TP from PsP (AUC=0.95). The time activity curve patterns and time to peaks were not different between the groups. Normalization of PET parameters to normal brain parenchyma were not helpful to differentiate the groups due to variability in radiotracer uptake in normal brain between subjects.

CONCLUSION
18F-Fluciclovine PET uptake can accurately differentiate PsP from TP in GBM patients, with even more accurate differentiation achieved when combined with MRI.
NIMG-46. TOWARDS PREDICTING TUMOR AGGRESSIVENESS WITH RADIOPATHOMIC ANALYSIS OF MULTI-PARAMETRIC ANATOMICAL, DIFFUSION-WEIGHTED, AND METABOLIC MRI IN PATIENTS WITH NEWLY-DIAGNOSED GLIOMAS
Authors: Adegbite Oluwaseun , Tran Nate , Molinaro Annette , Phillips Joanna J , Ellison Jacob , Li Yan , Luks Tracy , Shai Anny , Nair Devika , Pedoia Valentina , Villanueva-Meyer Javier , Berger Mitchel S , Hervey-Jumper Shawn L , Aghi Manish , Lupo Janine 
Published: November 2022

Abstract

INTRODUCTION
Pathologically aggressive tumor biology can extend beyond the contrast-enhancing or non-enhancing anatomical lesions in patients with glioma. Identification of malignant regions can help guide diagnosis and subsequent treatment planning. This study leverages a unique multi-parametric MRI dataset with tissue samples of known spatial coordinates to noninvasively predict cellular proliferation (KI-67) and a novel index of tumor aggressiveness (TAI), that combines proliferation, cellularity, and tumor-score.

METHODS
420 tissue samples were collected from 162 patients with newly-diagnosed glioma (47% IDH-wildtype). Clinical imaging consisted of T2-weighted, T2-FLAIR, T1-weighted pre- and post-contrast images, and apparent diffusion coefficient (ADC) and fractional anisotropy (FA) from diffusion-weighted imaging. Mean normalized imaging metrics were quantified from 5mm spheres centered at the location of the tissue sample. A single spectrum was reconstructed at the location of each tissue sample from 3D 1H-MR Spectroscopic Imaging (MRSI) before quantifying normalized metabolite peak-heights for choline, creatine, NAA, lactate/lipid, and relative indices. Univariate mixed-effects linear regression models were employed and features with p&lt; 0.2 were selected for subsequent model building. Support vector machine (SVM), random forest, and gradient boosting machine-learning algorithms were trained and tested on a ⅔-⅓ train-test split with 4-fold cross-validation in training to predict a high/low KI-67 and TAI.

RESULTS
Although none of the individual imaging metrics were significantly associated with KI-67 in the univariate analysis, all diffusion and several MRSI metrics (ncholine, nNAA, CNI, excess choline and creatine) were significantly associated with cellularity. Preliminary multivariate analyses to date suggest that the best radiopathomic model performance is achieved when an SVM was used along with T1-precontrast, nADC, and all metabolite levels (mean cross-validation AUC=0.73 and accuracy=.77).

CONCLUSION
Our results suggest that multi-parametric physiologic and metabolic MRI are useful for radiopathomic-mapping of tumor aggressiveness and are currently being optimized in a larger cohort.
NIMG-49. RADIO-PATHOMIC MAPS OF DE-NOVO GLIOBLASTOMA IDENTIFY PHENOTYPES OF TUMOR INVASION ASSOCIATED WITH PROGNOSIS
Authors: Bobholz Samuel , Lowman Allison , Duenweg Savannah , Winiarz Aleksandra , Kyereme Fitzgerald , Cochran Elizabeth , Connelly Jennifer , Mueller Wade , Agarwal Mohit , Banerjee Anjishnu , LaViolette Peter 
Published: November 2022

Abstract

PURPOSE
Although tumor is known to exist beyond the contrast-enhancing margin, a lack of access to pathological information beyond enhancement has hindered the study of non-angiogenic tumor characteristics and their effects on patient prognosis. This study tested the hypothesis that radio-pathomic maps of tumor characteristics developed using autopsy tissue samples can identify phenotypes relevant to patient survival and treatment outcomes.

METHODS
A dataset of autopsy tissue samples aligned to the MRI as ground truth from 65 glioma patients (training set n=43, test set n=22) was used to train machine learning models that predict and map tumor cellularity (Cell), extracellular fluid (ECF), and cytoplasm (Cyt) density following our previously published methodology (Bobholz et al. 2022). Cell, ECF, and Cyt maps were then generated from the pre-surgical MRI scans from an independent dataset of 80 glioblastoma patients. Each patient was separated into groups based on the appearance of tumor characteristics beyond the contrast-enhancing margin. Group phenotypes included Well-Circumscribed (WC) tumors with no tumor activity beyond contrast enhancement, Necrotic Front (NF) tumors with areas of necrosis extending beyond the tumor margin, Hypercellular Front (HF) tumors with areas of increased cellularity surrounding the tumor, and Hybrid Front (HYF) tumors with characteristics of both HF and NF tumors. A Cox regression was used to assess survival differences between phenotypes, controlling for treatment history.

RESULTS
Across the 80 patients, 22 were classified as WC, 14 were classified as HF, 24 were classified as NF, and 20 were classified as HYF. NF, HF, and HYF tumors each showed significant/trending reductions in survival when compared to WC tumors (HR=2.02, p=0.03; HR=2.0, p=0.06; and HR=1.75, p=0.09, respectively).

CONCLUSION
Radio-pathomic phenotypes identify characteristics beyond the contrast-enhancing margin that affect overall survival outcome in glioblastoma.