bluuebunny/crossref_metadata_2025 huggingface dataset:
PATH-62. RAMAN-BASED AI PLATFORM TO ACCELERATE THE DIAGNOSIS AND MANAGEMENT OF GLIOMAS VIA RAPID METHYLATION PROFILING
Authors: Lita Adrian , Sjöberg Joel , Păcioianu David , Siminea Nicoleta , Celiku Orieta , Păun Andrei , Gilbert Mark , Noushmehr Houtan , Petre Ion , Larion Mioara
Published: November 2023

BACKGROUND

DNA methylation profiling and subtyping of gliomas has become an integral part of the diagnosis and treatment of glioma patients but remains a challenge due to the sample preparation and time requirements of the existing methylation profiling technology. We hypothesized that machine learning and Raman spectroscopy, which creates fast molecular fingerprints of samples in situ based on chemical signatures rather than the use of exogenous dyes, can provide a fast alternative to the existing approaches for methylation profiling and classification of gliomas.

METHODS

Raman spectroscopy at the spatial resolution of less than 300nm was used for molecular fingerprinting of the regions of interest using 1mm2 Formalin-Fixed Paraffin-Embedded (FFPE) tissue spots from 45 patient samples with known LGm1 to LGm6 methylation subtypes. Spectral information (over 1738 frequencies) was used to construct tumor/non-tumor, IDH1WT/IDH1mut, and methylation-subtype classifiers. Oversampling was used to obtain subtype-balanced data distributions. Supervised wrapper methods and random forests were used to identify the top 20 most discriminatory Raman frequencies. Stimulated Raman spectroscopy was used to validate the findings.

RESULTS

We developed APOLLO - a novel platform based on spontaneous Raman spectroscopy and machine learning -- for predicting the DNA methylation subtypes of FFPE glioma tissue specimens. APOLLO discriminates tumors from non-tumor areas with 98% accuracy and discriminates IDH1mut versus IDH1WT tumors with 82% accuracy. APOLLO also achieved high discriminatory power between G-CIMP-high and G-CIMP-low molecular phenotypes (ROC of 0.75), subtypes of lower-grade IDH1mut gliomas with significantly different clinical outcomes. We determined that the Raman shifts important for discriminating IDH1mut versus IDH1wt tumors are associated with novel lipid-metabolism signatures of IDH1mut glioma.

CONCLUSIONS

The development of APOLLO allows fast, reliable, and accurate prediction of methylation subtypes of glioma which can speed diagnosis and, once validated on fresh tissue, can be implemented in the operating room.
PATH-64. COMPREHENSIVE CNS TUMOUR MOLECULAR DIAGNOSTICS USING THIRD GENERATION SEQUENCING
Authors: Patel Areeba , Hinz Felix , Dogan Helin , Goebel Kirsten , Schrimpf Daniel , Goeller Pauline , Ritter Michael , Pfeifer Lisa , Blume Christina , Berghaus Natalie , Payne Alexander , Goidts Violaine , Loose Matthew , Unterberg Andreas , Wick Wolfgang , Pfister Stefan , Sill Martin , von Deimling Andreas , Jones David , Schlesner Matthias , Sahm Felix
Published: November 2023

The WHO classification of CNS tumours 2021 recommends reporting a wide range of molecular alterations for WHO-compatible diagnoses. Conventional workflows warrant considerable investment and long turnaround times limited by batching. Nanopore sequencing enables long read sequencing, real-time targeting and simultaneous base modification detection with compact devices. Rapid-CNS2- a rapid, comprehensive adaptive sampling based sequencing pipeline with a turnaround time of 5 days was previously described. The ad-hoc methylation classification model employed by Rapid-CNS2 is limited to MNP v11 classes. This study presents an optimised Rapid-CNS2 and validation cohort that successfully reports hard-to-detect variants. We also present a whole genome sequencing workflow that affords direct upload to the MNP website for MNP v12 classification. We sequenced and analysed 156 samples from the Department of Neuropathology, University Hospital Heidelberg using Rapid-CNS2. RESULTS: were compared to NGS panel sequencing and methylation array analyses. Rapid-CNS2 showed improved resolution over NGS panel sequencing for CNAs. High accuracy was obtained for detection of SNV/Indels. Long reads spanning the breakpoint identified clinically relevant fusions in 10/10 cases. Subclonal SVs like EGFR vIII missed by NGS panel sequencing were detected with high confidence. Complete concordance was achieved for MGMT promoter methylation status and methylation classification for MNP v11 classes. The optimized Rapid-CNS2 workflow shortened the turnaround time to 30 hours from sample receipt and minimum input DNA required was reduced to 500ng. For WGS, samples were sequenced for 72h on a Promethion device. WGS enabled accurate reporting of SNVs, CNAs, SVs, MGMT promoter status in addition to MNP v12 classification directly from the website eliminating the need for ad-hoc training of methylation classification models. The presented nanopore sequencing based workflows provide feasible single assay alternatives to conventional molecular diagnostic approaches with the aim to make such analyses more accessible.
PATH-66. SEQ-ING THE SINES OF CENTRAL NERVOUS SYSTEM TUMORS IN CEREBROSPINAL FLUID DNA
Authors: Douville Christopher , Bettegowda Chetan
Published: November 2023

It is often challenging to distinguish cancerous from non-cancerous lesions in the brain using conventional diagnostic approaches. We here introduce an analytic technique called Real-CSF to detect cancers of the central nervous system from evaluation of DNA in the cerebrospinal fluid (CSF). Short interspersed nuclear elements (SINEs) from throughout the genome are PCR-amplified with a single primer pair and the PCR products are evaluated by next generation sequencing. Real-CSF assesses genome wide copy number alterations in each of 39 chromosome arms as well as focal amplifications of selected oncogenes. Real-CSF was applied to 280 CSF samples and correctly identified 67% of 184 cancers and 96% of 96 non-cancerous brain lesions. CSF analysis was considerably more sensitive than standard of care cytology and plasma cell-free DNA analysis in the same patients. Real-CSF therefore has the capacity to be used in combination with other clinical, radiologic, and laboratory-based data to inform the diagnosis and management of patients with suspected cancers of the brain.
NIMG-01. AI-BASED ASSESSMENT OF BRAIN VOLUME DECREASE AFTER SRS AND WBRT
Authors: Thiele Frederic , Kawula Maria , Katzendobler Sophie , Bodensohn Raphael , Kurz Christopher , Landry Guillaum , Weller Jonathan , Niyazi Maximilian
Published: November 2023

BACKGROUND

Stereotactic radiosurgery (SRS) for 4-10 brain metastases has been shown to be associated with prolonged survival as compared to whole brain radiotherapy (WBRT). Brain volume decrease after WBRT is a marker for poor survival. We aimed at comparing brain volume decrease in patients treated with either SRS or WBRT.

METHODS

Patients treated with SRS were drawn from the prospective dataset of the STEREOBRAIN study (DRKS00014694) that recruited from 2017 to 2020. Patients that received WBRT for 4-10 brain metastases were included retrospectively from 2012 - 2017. Images were registered to the MNI305 space utilizing the Advanced Normalization Tools (ANTs) Toolkit. Brain extraction was performed using the deep-learning based HD-BET UNet. Anatomical brain structures were labelled by employing the current state-of-the-art pretrained transformer based UNesT network using the MONAI deep-learning framework. Labels were bundled and analysed. Last pre-radiotherapy scans were compared with the last post-radiotherapy scans. The proportion of the ventricular system to the total intracranial volume was implemented as a measure of brain volume decrease.

RESULTS

Overall, 65 patients were included. 29 patients (45%) received SRS and 36 patients (55%) were treated with WBRT. Patients treated with SRS showed no significant increase in the volume of the ventricular system compared to the total intracranial volume (p= 0.13), whereas patients in the WBRT cohort did (p< 0.01). The mean relative volume increase of the ventricular system was 33% in the SRS cohort. In the WBRT cohort, the mean increase was 54%. The median time between the two scans was 414 days in the SRS cohort and 244 days in the WBRT cohort.

CONCLUSION

Brain volume decrease is less extensive in patients treated with SRS than WBRT. The clinical implication of this finding, e.g., prolonged survival and better clinical status, is yet to be determined and quantified.
NIMG-02. ADVERSE RADIATION EFFECT VERSUS TUMOR PROGRESSION FOLLOWING STEREOTACTIC RADIOSURGERY FOR BRAIN METASTASES: IMPLICATIONS OF RADIOGRAPHIC UNCERTAINTY
Authors: Salans Mia , Ni Lisa , Boreta Lauren , Theodosopoulos Philip , Morin Olivier , Braunstein Steve
Published: November 2023

Despite efforts from RANO to standardize treatment response reporting, adverse radiation effect (ARE) following stereotactic radiosurgery (SRS) for brain metastases (BM) remains challenging to distinguish from tumor progression (TP) due to radiographic uncertainty (RU), often necessitating serial imaging until definitive diagnosis (DD) is resolved. We characterized management and implications of RU after BM irradiation for multiple primary tumor histologies. We identified 138 BM cases reviewed at our multi-disciplinary SRS Tumor Board (TB) for RU of ARE versus TP on MRI following SRS between 2015-2022. Target diameter (mm), histology, location, and SRS dose (Gy) on initial treatment and lesion diameter, associated symptoms, and supportive medications at the time of TB presentation were extracted from the medical record. Final lesion etiology, use of any intervention, and neurologic deficits upon DD were documented. Time from RU to DD was calculated. Median time from SRS to initial RU was 11.3 months (IQR 5.5-18.2). Median RU lesion diameter was 14.0 (IQR 8.0-20.0). At the time of RU, 43% of patients were symptomatic, 28% and 4% requiring steroids and bevacizumab, respectively. Time to DD following RU was > 6 and 12 months in 28% and 8% of patients, respectively (maximum 47 months). Median lesion diameter at DD was 16.0 mm (IQR 10.3-24.0). Most (54%) had a DD of ARE, while 41% had TP; 23% and 77% were diagnosed pathologically and radiographically, respectively. Upon DD, 41% underwent local intervention with surgery and/or re-irradiation and 25% had a new neurologic deficit, including weakness (7%), ataxia (5%), and aphasia (4%). In an interdisciplinary setting, it took > 6 months to reach a DD after RU in > 25% of patients previously irradiated for BM. Diagnostic uncertainty and delay may lead to sub-optimal outcomes and symptom burden. Improved characterization of post-SRS imaging findings is needed in this population.
NIMG-09. APPLICATION OF FRACTIONAL TUMOR BURDEN MAPPING TO MONITOR GLIOBLASTOMA PROGRESSION IN THE PHASE 1 TRIAL OF GALLIUM MALTOLATE
Authors: Zoss Casey , Connelly Jennifer , Chitambar Christopher , Schmainda Kathleen
Published: November 2023

BACKGROUND

To address the need for improved glioblastoma (GBM) therapeutics, a Phase 1 trial of gallium maltolate (GaM) for recurrent GBM is ongoing. GaM targets GBM iron metabolism, representing a novel therapeutic mechanism to treat GBM. Monitoring GBM progression is typically accomplished by standard MRI protocols. However, distinguishing progression from treatment effect is often difficult using standard MRI alone; this is especially true for experimental therapeutics. Fractional tumor burden (FTB) mapping incorporates dynamic susceptibility contrast perfusion MRI to generate spatial and quantifiable tumor likelihood estimates. Here, we present three cases from the Phase I trial of GaM to illustrate application of FTB mapping in the clinical trial setting.

METHODS

Patients enrolled in the GaM trial receive pre-trial baseline imaging and subsequent imaging at 8-week intervals. For each imaging timepoint, an FTB map was created from tissue-validated thresholds of standardized relative cerebral blood volume (sRCBV) in areas of enhancement as determined by pre/post T1 subtraction.

RESULTS

Case #1 illustrates low FTB-determined tumor probability in a patient with minimal disease who did not progress while on trial for > 33 weeks. Case #2 shows an increase in tumor probability concurrent with radiographic and pathology-confirmed progression soon after initiating GaM. Case #3 demonstrates an increase in tumor probability soon after GaM initiation which preceded an increase in volume by > 10 weeks; GBM progression was confirmed by pathology.

CONCLUSIONS

The presented cases illustrate the utility of FTB mapping for monitoring GBM progression in the setting of GaM treatment. FTB maps could predict disease progression before standard MRI in some patients. Our experience implicates FTB mapping as an important imaging tool in future GBM clinical trials. The cases add to previous reports that FTB is useful in distinguishing progression from treatment effect with standard treatment regimens.
NIMG-15. COMBINED ADVANCED IMAGING AND MGMT STATUS FOR DISTINCTION BETWEEN EARLY TUMOR PROGRESSION AND PSEUDOPROGRESSION IN GLIOBLASTOMA
Authors: Diaz Maria , Joanta-Gomez Adela , Torres Denisse , Furnari Julia , Matari Nahill , Canoll Peter , Lignelli Angela , Lassman Andrew
Published: November 2023

BACKGROUND

Within 3-6 months of completing initial chemoradiotherapy, up to 50% of glioblastomas (GBM) develop worsening contrast enhancement on surveillance imaging, which could represent early progression (EP) or pseudoprogression (PsP). Reports suggest EP is more common in MGMT unmethylated (uMGMT) cases. While multiple advanced imaging studies have tried to address this issue (including magnetic resonance with perfusion [MRP], with spectroscopy [MRS], and FDG-PET), no non-invasive test reliably differentiates EP from PsP, yet the distinction is critical for subsequent management. We aimed to develop a multiparametric score including advanced imaging and MGMT status to improve interpretation.

METHODS

We retrospectively reviewed records of patients diagnosed with GBM from 2016-2022 who had changes on anatomic imaging concerning for EP vs. PsP ≤6 months after chemoradiotherapy and underwent ≥ 2 advanced imaging sequences (MRP, MRS, FDG-PET); definitive distinction between EP and PsP was made by either histology from surgical resampling or subsequent clinico-radiographic evolution. Associations between clinical factors and EP were investigated with logistic regression. Sensitivity and specificity of each imaging modality and of a composite score (1 point each for MRP consistent with EP, MRS consistent with EP, and uMGMT) were calculated.

RESULTS

46 evaluable patients (57% male; median age 58.5 years, range 31-80) were included; outcome (EP in 29 [63%], PsP in 17 [37%]) was determined histologically and clinically in 15 (33%) and 31 (67%) of cases, respectively. In multivariate analysis, uMGMT was predictive of EP (OR=2.63, 95% CI=1.29-37.55, p< 0.05). Sensitivity/specificity to predict EP were 78%/77% for uMGMT, 76%/29% for MRP, 85%/67% for MRS, 86%/0% for FDG-PET (8 patients) and 88%/75% for composite score of 2-3 (vs. 0-1).

CONCLUSION

Combining MRS, MRP and MGMT results can improve accuracy in distinguishing EP from PsP in GBM. MGMT status should be incorporated in the interpretation of advanced imaging to distinguish EP from PsP.
NIMG-20. ASSESSMENT OF RESPONSE TO REGORAFENIB IN RECURRENT GLIOMA PATIENTS USING FET PET AND MRI INCLUDING ADC VALUES
Authors: Werner Jan-Michael , Lohmann Philipp , Kabbasch Christoph , Wollring Michael , Tscherpel Caroline , Stoffels Gabriele , Goldbrunner Roland , Langen Karl-Josef , Fink Gereon , Galldiks Norbert
Published: November 2023

INTRODUCTION

Currently, data on O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET and MRI parameters for the evaluation of response to regorafenib in glioma patients remain scarce.

METHODS

Twenty patients (age range, 30-72 years) with recurrent CNS WHO grade 3 or 4 gliomas (glioblastoma, 85%) were treated according to the REGOMA trial. FET PET and MRI were performed at baseline and follow-up after the second cycle. Static FET PET parameters comprised tumor-to-brain ratios (TBR) and metabolic tumor volumes (MTV). Parameters derived from dynamic FET PET acquisition were time-to-peak and slope. MRI response assessment was based on RANO criteria. Additionally, various apparent diffusion coefficients (ADC) parameters were obtained from diffusion-weighted MRI. Thresholds derived from FET PET and ADC parameters were defined using ROC analyses to predict an overall survival (OS) of ≥6 months. The predictive values of FET PET parameters, ADC values, and RANO criteria were subsequently evaluated using univariate and multivariate survival estimates.

RESULTS

Patients received a median of three regorafenib cycles (range, 2-10 cycles). After treatment initiation, the median follow-up was 8.6 months (range, 3.2-27.3 months). After two cycles of regorafenib, a reduction of mean TBR values by ≥10% predicted significantly longer OS (9.9 vs. 5.3 months; P=0.023). Additionally, absolute mean TBR values ≤2.0 at follow-up were prognostic and associated with a significantly longer OS (10.6 vs. 4.5 months; P=0.007). In contrast, MTV, dynamic PET parameters, RANO criteria, and ADC values were not predictive for response or were prognostic (all P >0.05). Multivariate survival analyses revealed that relative mean TBR changes were most potent in predicting response to regorafenib (P=0.038; HR, 0.246) and absolute mean TBR values for prognostication (P< 0.001; HR, 0.005).

CONCLUSION

In contrast to MRI metrics, FET PET parameters are clinically valuable for identifying responders to regorafenib early after treatment initiation and helpful for prognostication.
NIMG-21. SERIAL QUANTITATIVE MRI RADIOMICS SIGNATURE FOR PREDICTION OF SURVIVAL IN GLIOBLASTOMA – A PILOT STUDY
Authors: Chen Cecil , Martin Philip , Koh Eng-Siew , Brighi Caterina , Aly Farhannah , Rai Robba , Holloway Lois , Metcalfe Peter , Pillay Sugendran
Published: November 2023

INTRODUCTION

Radiomics in glioblastoma (GBM) imaging incorporates mathematical and statistical quantification of complex imaging features as surrogate biomarkers of tumour physiology. Delta-radiomics extends this capability by monitoring changes in these features over time. This study aims to evaluate selected radiomic and delta-radiomic features of diffusion-weighted imaging (DWI) as potential early predictors of overall survival (OS) in GBM patients undergoing adjuvant chemo-radiotherapy (aCRT).

METHODS

Imaging and data from n=12 newly diagnosed GBM patients prospectively recruited at Liverpool Hospital, New South Wales, were retrospectively analysed. Patients underwent serial MRI via 3.0T Siemens Magnetom-Skyra scanner, including anatomical and DWI sequences, before aCRT (baseline), and at 3 (FU1) and 6 weeks (FU2) post aCRT commencement. Gross tumour volume (GTV) was manually segmented on contrast-enhanced T1-weighted images. Four first-order histogram radiomic features (mean, skewness, entropy and 10th-percentile) and volume were extracted from the GTV on DWI sequences at each timepoint. Delta-radiomic features were calculated from the difference between measurements at baseline and each follow-up. Linear correlation between OS versus baseline and delta-radiomic features were calculated with Pearson’s coefficient (r). Statistically significant correlations were tested on an external validation dataset of n=8 GBM cases from The Cancer Imaging Archive (ACRIN-FMISO-Brain and ACRIN-DSC-MR-Brain datasets).

RESULTS

A significant positive correlation was found between OS and delta-entropy at FU2 (r = 0.639, p = 0.02). No significant correlation was found between OS and baseline or delta mean, skewness, or 10th percentile (p > 0.05). No significant correlation was found between OS and delta-volume at FU1 (r = 0.134, p = 0.68) or FU2 (r = 0.100, p = 0.76).

CONCLUSION

Our results indicate a potential utility of delta-entropy for prediction of overall survival.

RESULTS

will be validated on an external dataset. Further evaluation of radiomic and delta-radiomic features on a larger sample size is warranted.
NIMG-22. COMPARISON OF NON-INVASIVE, ML-GENERATED WHOLE-BRAIN SPATIAL RADIOPATHOMIC MAPS DERIVED FROM ANATOMICAL AND DIFFUSION-WEIGHTED MRI ON PATIENTS WITH NEWLY DIAGNOSED-GLIOMA
Authors: Adegbite Oluwaseun , Tran Nate , Molinaro Annette , Phillips Joanna , LaViolette Peter , Bobholz Samuel , Ellison Jacob , Li Yan , Luks Tracy , Shai Anny , Nair Devika , Villanueva-Meyer Javier , Connelly Jennifer , Berger Mitchel , Hervey-Jumper Shawn , Aghi Manish , Chang Susan , Lupo Janine
Published: November 2023

INTRODUCTION

Spatial heterogeneity in the glioma microenvironment is difficult to capture through singular biopsy samples. Identification of malignant tumor regions can help guide diagnosis and treatment planning. This study compares radiopathomic maps from 2 strategies derived from anatomical and diffusion-weighted MRI: 1) a support vector machine model trained on an MRI dataset with tissue samples of known spatial coordinates to generate spatial maps of probability of KI-67 and cellularity, and 2) a bagged random-forest model derived from 40+ person glioma brain bank of autopsy tissue coregistered to end-of-life MRI to generate spatial maps of cellularity and tumor probability (TPM). We hypothesize that TPMs from autopsy samples will correlate with KI-67 predictions, while cellularity values among methods will correlate.

METHODS

Spatial maps of tumor pathology from autopsy- and tissue sample-based models were generated on 55 patients newly-diagnosed with glioblastoma that were scanned with anatomical, diffusion-weighted, and metabolic imaging. Mean values were extracted from each map within the T2-hyperintense, non-enhancing lesion (NEL), the contrast-enhancing lesion (CEL), normal-appearing white matter (NAWM), and 5mm diameter spheres centered at the location where tissues were taken. Spearman correlation analysis was used to elucidate the strength of the linear relationship within the selected regions between the two maps.

RESULTS

Correlations between KI-67 and TPM values were highest and most significant at the tissue sample locations and CEL (ρ=0.306, p=0.002 and ρ=0.312, p=0.044 respectively). Cellularity maps generated from the autopsy-based model showed no significant correlation with newly diagnosed cellularity values at tissue sample locations, potentially highlighting the influence of treatment.

CONCLUSION

This study examines the current state of ML-generated spatial mapping, highlighting similarities within CEL, but need to account for the effects of subsequent treatment and progression when comparing tumor beyond the CEL between models derived between different time points.
NIMG-27. GLIOBLASTOMA IN THE MAKING? ADVANCED IMAGING TELLS "MOLECULAR GLIOBLASTOMA" APART FROM ASTROCYTOMA
Authors: Griessmair Michael , Metz Marie-Christin , Zimmer Claus , Wiestler Benedikt
Published: November 2023

The fifth WHO classification of tumors of the CNS allows the diagnosis of glioblastoma using specific molecular markers, even if the classical histological criteria (necrosis and neoangiogenesis) are not fulfilled. Since such cases also tend to lack blood-brain barrier disruption and necrosis on conventional imaging, these can be mistaken for low-grade astrocytomas. We investigated the potential of advanced imaging to capture tumor biology and thus reliably distinguish between those entities already preoperatively. Multimodal preoperative 3T-MRI scans were collected from 147 glioblastoma, 4 astrocytomas grade 4, 7 “Molecular glioblastoma” (molGBM) grade 4, 9 astrocytomas grade 2, and 12 astrocytomas grade 3. From AI-based multi-compartimental tumor segmentations, advanced imaging metrics from perfusion- and diffusion-imaging were automatically extracted. Two-sample t-test and one-way ANOVA analysis was performed to test for significant differences between apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV). Interestingly, rCBV (signifying neoangiogenesis) was significantly higher in molGBM as opposed to astrocytomas for the 5th percentile as well as for mean and median values (p < 0.05). ADC values were consequently lower (indicating higher cellularity) in molGBM than in astrocytomas grade 2 and 3 in the 95th percentile (p < 0.05). Although no molGBM showed contrast-enhancement initially, one untreated case showed a flaccid barrier disruption at 30d follow-up. Interestingly, the molecular imaging at the earlier timepoint showed significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.013, ANOVA), which indicates highly active tumor portions. Perhaps it is precisely these areas that are on the verge of barrier disruption. Our results support the hypothesis that molGBM are truly early glioblastomas. Better understanding the molecular mechanisms involved in the transition to “classical” glioblastoma promises to provide important insight into tumor biology and potential therapeutic targets.
NIMG-30. DEEP LEARNING SEGMENTATION OF INFILTRATIVE AND ENHANCING CELLULAR TUMOR IN POST-TREATMENT GLIOBLASTOMA PATIENTS WITH MULTI-SHELL DIFFUSION MRI
Authors: Gagnon Louis , Gupta Diviya , Mastorakos George , White Nathan , Goodwill Vanessa , McDonald Carrie , Beaumont Thomas , Conlin Christopher , Seibert Tyler , Hattangandi-Gluth Jona , Kesari Santosh , Schulte Jessica , Piccioni David , Dale Anders , Farid Niky , Rudie Jeffrey
Published: November 2023

Multimodal MRI is used for the evaluation of tumor burden in glioblastoma (GBM) patients after surgical resection, radiation, and chemotherapy. However, it can be challenging to identify non-enhancing infiltrative tumor and differentiate recurrent enhancing tumor from post-treatment changes. Restriction spectrum imaging (RSI), an advanced multishell diffusion technique, has shown promise in distinguishing cellular tumor from edema and enhancing post-treatment changes including pseudoprogression and radiation necrosis. We developed a convolutional network (nnUNet) that incorporates traditional multimodal MRI with DSC perfusion and RSI to detect and quantify enhancing and nonenhancing cellular tumor in post-treatment glioblastoma patients. This cellular tumor segmentation network was evaluated in a cohort of 186 post-treatment GBM patients (55.5 +/- 13.7 years, 158 male) with 243 timepoints using 5-fold cross validation. Cellular tumor volumes were then used to predict overall survival (OS) and progression free survival (PFS) in 94 patients with imaging within 3 months of initial surgery. Accuracy for segmenting cellular tumor as measured by the Dice-similarity coefficient was 0.77 (IQR 0.55-0.87) and the AUC of the ROC curve for detecting residual/recurrent tumor compared to post-treatment changes was 0.86. The predicted cellular tumor volumes were an independent hazard over age, sex, GTR status and conventional enhancing residual tumor for both OS (p=0.0003) and PFS (p=0.0004). The tumor segmentation network was validated in an external dataset of 22 GBM patients (55 timepoints) with a median Dice of 0.73 and AUC of 0.91. Survival prediction was validated in a different external dataset of 70 post-treatment GBM patients, with cellular tumor volumes being an independent predictor of OS (p=0.03). In conclusion, deep learning models incorporating advanced imaging can accurately segment enhancing and nonenhancing cellular tumor, which can help distinguish recurrent/residual tumor from post-treatment changes and predict OS and PFS.
NIMG-32. MULTI-MODAL ANALYSIS UNCOVERS DIFFERENTIALLY REGULATED PATHWAYS ASSOCIATED WITH RADIO-PHENOTYPES IN PEDIATRIC LOW-GRADE GLIOMA
Authors: Kazerooni Anahita Fathi , Kraya Adam , Rathi Komal , Haldar Debanjan , Mahtabfar Aria , Khalili Nastaran , Familiar Ariana , Kim Meen Chul , Bagheri Sina , Anderson Hannah , Ware Jeffrey B , Storm Phillip , Davatzikos Christos , Vossough Arastoo , Resnick Adam , Nabavizadeh Ali
Published: November 2023

INTRODUCTION

Pediatric low-grade glioma is comprised of a broad variety of histological subtypes with heterogeneous responses to standard-of-care treatments. Understanding the biological pathways underlying clinical radiographic appearances, or radio-phenotypes, may facilitate precision diagnostics prior to the initiation of any interventions, thereby, reducing the risk of co-morbidities while improving patient outcome. Here, we aim to comprehensively harness the high-throughput multi-modal data available through Children’s Brain Tumor Network (CBTN) to elucidate the pathways that form radio-phenotypic traits of pLGG.

METHODS

On a cohort of 165 patients with pLGG, 881 radiomic features were extracted from multiparametric MRI sequences. We applied principal component analysis (PCA) followed by K-Means clustering to the radiomic features along with clinical variables of age, gender, and tumor location to group the patients into distinct imaging subtypes. We used whole transcriptomic data from OpenTargets to compare differential expression and co-expression of network- and pathway-level properties via Gene Set Enrichment Analysis (GSEA), and Gene Sets Net Correlations Analysis (GSNCA) among the discovered imaging subtypes.

RESULTS

Three imaging subtypes of pLGG were identified, among which subtype1 tumors showed increased proliferative capacity and invasive potential. This was suggested by higher expression of cell cycle regulatory, extracellular matrix (ECM) remodeling, and cell migratory pathways in subtype1 than subtypes 2 and 3. Furthermore, subtype1 exhibited differential TNF/TNFR signaling compared to subtype2, potentially related to differential regulation of pro-tumorigenic immune pathways, and differential regulation of TGF-beta and Aurora Kinase A signaling compared to subtype3, associated with differences in proliferative pathways. Subtypes 1 and 2 exhibit higher pro-tumorigenic cytokine expression while subtype3 involves higher expression of neurotransmitter release and neuronal activity, which may be targetable.

CONCLUSIONS

Our multi-modal radiogenomic analysis unraveled molecular underpinnings that give rise to the formation of distinct imaging phenotypes, with the potential to inform personalized treatments for children with brain tumors.
NIMG-35. RADIO-PATHOMIC MAPS OF TUMOR PROBABILITY IDENTIFY GLIOBLASTOMA INVASION BEYOND 5-ALA GUIDED RESECTION MARGINS THAT EVENTUALLY EXHIBIT TUMOR RECURRENCE
Authors: Winiarz Aleksandra , Bobholz Samuel , Lowman Allison , Duenweg Savannah , Stebbins Margaret , Flatley Michael , Nath Biprojit , Kyereme Fitzgerald , Connelly Jennifer , Coss Dylan , Krucoff Max , Banerjee Anjishnu , LaViolette Peter
Published: November 2023

Current standard of care for glioblastoma includes surgery followed by chemotherapy and radiation, with extent of resection strongly correlated with survival. There is a need to improve the detection of tumor invasion beyond traditional imaging methods, as the full extent of tumor is known to be underestimated. Fluorescence-guided surgery with 5-Aminolevulinic acid (5-ALA) allows surgeons to visualize tumor cells beyond what is seen within traditional MR imaging margins. In this study, we compared tumor probability maps (TPMs) that detect tumor outside of contrast enhancement (CE) to the 5-ALA-guided resection cavity in glioblastoma patients. 3 pathologically confirmed glioblastoma patients that followed standard of care and underwent 5-ALA surgery were included. Patient 1 was a 56-year-old male with radiographic recurrence at 26 days, patient 2 was a 61-year-old male with radiographic recurrence at 130 days, and patient 3 was a 72-year-old male with cystic recurrence at 84 days, all post 5-ALA surgery. A previously published algorithm, using T1, T1C, FLAIR, and ADC as input and autopsy tissue as ground truth, was used to generate TPMs. Pre-surgical TPMs were qualitatively compared to pre-surgical CE, post-5-ALA surgical resection cavities, and radiographic recurrence seen as CE. In patients 1 and 2, TPMs identified areas suspicious of tumor that was not resected and later exhibited radiographic recurrence. Patient 3 had cystic recurrence only identified on post-resection T1C. In all patients, the extent of 5-ALA resection was greater than CE volume, but smaller than TPM identified tumor. These findings suggest that there was residual tumor that was unidentified via 5-ALA and traditional imaging but was identified by the TPMs. Future studies could utilize these maps in conjunction with 5-ALA to maximize surgical resections and prolong overall survival.
NIMG-42. RADIOIMMUNOMIC SIGNATURES IN PEDIATRIC LOW-GRADE GLIOMA FOR NON-INVASIVE IDENTIFICATION OF IMMUNOTHERAPEUTIC TARGETS
Authors: Kazerooni Anahita Fathi , Kraya Adam , Rathi Komal , Khalili Nastaran , Haldar Debanjan , Familiar Ariana , Kim Meen Chul , Bagheri Sina , Anderson Hannah , Foster Jessica , Storm Phillip , Davatzikos Christos , Ware Jeffrey B , Vossough Arastoo , Resnick Adam , Nabavizadeh Ali
Published: November 2023

INTRODUCTION

Tumor immune microenvironment (TIME) plays a key role in response to anti-tumor therapies. Therefore, detailed characterization of TIME is crucial for patient stratification and enrollment onto emerging immunotherapies. As standard-of-care treatments are not feasible or confer devastating long-term morbidity for pediatric low-grade glioma (pLGG), non-invasive quantification of the TIME using radiomic analysis, may guide treatment decisions. On the largest available transcriptomic and imaging data in pLGGs, provided through Children’s Brain Tumor Network (CBTN), this data-driven study aims to discover immunological profiles of pLGG that are meaningfully related to biomarkers of tumor immune response, and radioimmunomic signatures that are predictive of immunological profiles.

METHODS

Enrichment of immune and stromal cell types and pathways in 502 subjects were inferred using xCell algorithm applied to transcriptomic data and the tumors were then clustered via consensus clustering approach. Tumor inflammation signature (TIS), as a biomarker of response to anti-PD-1 blockade, was compared across the immunological clusters. Quantitative radiomic features were extracted from the segmented tumor regions on multiparametric MRI scans of 155/502 patients. Cross-validated support vector machines with forward feature selection were trained on radiomic features using one-versus-the-rest approach to predict the immunological groups.

RESULTS

Three immunological clusters, i.e., immune-cold, -altered, and -hot were found, with different levels of enrichment in immune and microenvironment scores, CD4 T-cells, and macrophages. Significantly higher TIS values were found in immune-hot and -altered compared to immune-cold tumors (p= 1.2e-8 and p= 7e-16, respectively). Radioimmunomic models yielded average AUC of 0.75 for one-versus-the-rest differentiation of the immunological clusters.

CONCLUSIONS

The proposed analysis revealed three distinct immunological groups in pLGGs, with immune-hot tumors more likely to respond favorably to immunotherapies. Furthermore, non-invasive radioimmunomic signatures were shown to potentially stratify the patients based on their TIME, which upon further development and validation, could inform treatments for pLGGs.
NIMG-43. A 57-YEAR-OLD MALE WITH PRIMARY GLIOBLASTOMA TREATED WITH LASER INTERSTITIAL THERMAL THERAPY: IMAGING AND AUTOPSY FINDINGS
Authors: Lowman Allison , Winiarz Aleksandra , Bobholz Samuel , Duenweg Savannah , Stebbins Margaret , Flatley Michael , Nath Biprojit , Kyereme Fitzgerald , Coss Dylan , Krucoff Max , Connelly Jennifer , LaViolette Peter
Published: November 2023

INTRODUCTION: Glioblastoma (GBM) is an aggressive primary brain cancer with significant resistance to the current therapeutic approach of chemotherapy and radiotherapy, jointly known as chemoradiation (CRT). Magnetic hyperthermia therapy (MHT) is a promising therapy for GBM that can be used to perform multiple sessions of non-invasive, localized hyperthermia by activating locally delivered magnetic iron oxide nanoparticles (MIONPs) with an external alternating magnetic field (AMF). In this study, MHT-mediated enhancement of CRT was evaluated in murine and human glioma cell lines both in cell culture and in rodents.
NIMG-49. INTRAOPERATIVE 5-ALA INTENSITY ANALYSIS OF GLIOMA USING IMAGE J
Authors: Kon Takashi , Kobayashi Yusuke , Shimizu Katsuyoshi , Mizutani Tohru , Sato Yosuke
Published: November 2023

PURPOSE: The 5 aminolevulinic acid (5-ALA) is used for intraoperative tumor visualization in neurosurgery. We hypothesized that glioma may vary in malignancy according to the brightness of 5-ALA. We quantified the brightness of 5-ALA and compared it with the pathological results of glioma. MATERIALS AND METHODS: From 2019 to 2023, we investigated 35 glioma patients who underwent surgery with 5-ALA. Twenty-three cases of glioblastoma (GBM), four cases of anaplastic astrocytoma (AA), three cases of oligodendroglioma (OL), one case of anaplastic oligodendroglioma (AO), and four cases of low grade glioma (LGG) were examined. The pathological diagnosis was based on classification of WHO 2016. The 5-ALA was administered before surgery, and the 5-ALA brightness were quantified. RESULTS: In GBM, the mean brightness was 134.5 ± 65.4, except for one negative case. AA showed the mean brightness with 180.5 ± 51.6. Three cases of OL showed the mean brightness with 78.6 ± 32.7. AO showed the brightness with 153. All LGGs showed negative in the brightness. CONCLUSION: The 5-ALA showed higher brightness in GBM , AA, AO and negative in LGG. In the future, we will accumulate cases and add further studies.
NIMG-58. PET IMAGING AS A RELIABLE INDICATOR FOR EVALUATING BEVACIZUMAB TREATMENT RESPONSE IN GBM
Authors: Miyake Keisuke , Takahiro Kanda , Suzuki Kenta , Fujimori Takeshi , Toyota Yasunori , Ogawa Daisuke , Hatakeyama Tetsuhiro , Okauchi Masanobu , Kawanishi Masahiko
Published: November 2023

OBJECTIVE

PET scans are crucial for glioma diagnosis and treatment planning, but assessing the efficacy of Bevacizumab (Bev) treatment using MRI alone is challenging. Our study aimed to evaluate the effectiveness of Bev-based glioblastoma treatment using PET scans.

METHODS

We included ninety glioblastoma patients treated with Bev between July 2013 and May 2023. Patients were divided into three groups: the first group received Bev in addition to the Stupp regimen after biopsy or subtotal resection (first-dose group), the second group received Bev after biopsy followed by tumor resection (neoadjuvant group), and the third group received the Stupp regimen followed by TMZ + Bev at recurrence (recurrent group). PET scans (FDG, MET, FLT, and FMISO) were performed before and 4 weeks after starting Bev treatment. Tumor-to-normal ratio (TNR) was calculated for FDG, MET, and FLT, and tumor-to-blood ratio (TBR) was determined for FMISO. We used the Cox proportional hazards model to assess the percent change in TNR, TBR, and metabolic tumor volume (MTV) as prognostic factors.

RESULTS

The median PFS and OS (month) from Bev treatment were as follows: first-dose group (PFS: 8.87, OS: 12.53), neoadjuvant group (PFS: 16.53, OS: 22.13), and recurrent group (PFS: 4.0, OS: 8.0). In the first-line group, significant differences were found in the percent change in MTV for MET, FLT, and FMISO. In the recurrent group, significant differences were observed in the percent change in MTV for FDG and MET, as well as in FDG TNR and FMISO TBR. In the neoadjuvant group, significant differences were found in the percent change in MTV for MET and FLT.

CONCLUSION

Neoadjuvant Bev treatment led to prolonged PFS and OS in glioblastoma patients. Decreases in MET MTV change rate and FMISO TBR change rate were identified as potential indicators for assessing Bev treatment efficacy after recurrence.
NIMG-61. RADIOLOGICAL, CLINICAL, AND MOLECULAR ANALYSES UNRAVEL DISTINCT SUBTYPES OF ADULT GRADE 4 BUTTERFLY GLIOMAS AFFECTING THE PROGNOSIS
Authors: Shibahara Ichiyo , Tanihata Yoko , Fujitani Kazuko , Handa Hajime , Kumabe Toshihiro
Published: November 2023

Gliomas located at the corpus callosum (CC) and invading the bilateral hemispheres is known as butterfly gliomas (bG). Images of bG are frequently used as the hallmark of glioblastoma (GB); however, the molecular background and origins of bG remain unknown. We collected 37 bG patients, including 32 cases of GB and 5 cases of astrocytoma, WHO grade 4, IDH-mutant. Our dataset included extremely rare sequential radiological imaging before receiving a definitive diagnosis of bG. One case emerged from CC and subsequently became bG, whereas five cases emerged from the cerebral hemisphere and became bG, suggesting distinct radiological origins exist in bG. Reflecting this observation to further analysis, we subdivided the cohort into CC-type (n = 15) and hemispheric-type (n = 22) based on the ratio calculated by the tumor volume at CC and hemisphere. Survival analysis presented that CC-type was significantly poorer overall survival (OS) than hemispheric-type (P = 0.010), indicating that bG has clinically distinct two subtypes. Molecular analyses revealed that TERT promoter mutations and IDH1 mutations were observed in 73.3% and 0% in the CC-type, whereas 36.4% and 22.7% in the hemispheric-type, respectively. Other alterations such as MGMT promoter methylation, EGFR amplification/gain, CDKN2A hemi/homozygous deletion, and PTEN hemi/homozygous deletion remained the same between two groups. None of the patients had H3F3A, HIST1H3B, or BRAF mutations. In the hemispheric-type, the multisampling of hemispheric and CC specimens revealed accumulating alterations in the CC lesions, indicating an invasive trajectory from the hemisphere to the CC region. For the validation, we reviewed 993 MRI obtained from the public datasets (TCGA-GBM, CPTAC-GBM, IvyGap, and UPenn-GBM) and found the same trend: CC-type presented poor OS. bG is not a sole subtype with just extensive invasion from the hemisphere. Our results highlight the pathophysiology of bG and may influence its management.
NIMG-63. GAMMA-BAND MODULATIONS OF ELECTROCORTICOGRAM (ECOG) INDUCED BY COGNITIVE-LINGUISTIC TASKS DURING AWAKE CRANIOTOMY FOR FEASIBLE FUNCTIONAL LANGUAGE MAPPING
Authors: Tasnim Israt , Asman Priscella , Swamy Chandra Prakash , Hall Matthew , Noll Kyle , Connelly Katherine , Tummala Sudhakar , Ince Nuri Firat , Prabhu Sujit
Published: November 2023

INTRODUCTION

Intraoperative functional language mapping has uncertainty in predicting language function and post-surgical outcomes. We study the feasibility of functional mapping using electrocorticogram (ECoG) gamma-band modulations induced by linguistic tasks having different complexity levels.

METHODS

Five subjects with left temporal lobe glioma underwent resection involving awake language mapping using a 4x8 ECoG electrode grid. A MATLAB/Simulink based real-time software system was used to map task-induced gamma-band modulations as 2D heat maps. Tasks included verbally responding to single word/tone categorization; object, action, written descriptive and auditory naming respectively. Auditory stimuli were provided during word/tone categorization (duration 300~500ms) and auditory naming tasks ( > 1s). Other tasks provided visual stimuli (line drawings or written phrases). Bipolar DCS (2~6 mA, 60Hz, 2s) was applied at different electrode pairs while repeating the naming tasks.

RESULTS

Cortical regions activated by word stimuli and the auditory naming task were similar; superior, middle temporal gyri (STG, MTG). Visual naming tasks modulated posterior MTG (pMTG) and STG (written naming). Reproducible speech arrests occurred during different naming tasks while stimulating specific electrode pairs, even though not all electrodes had strong task-specific activations. Considerable inter-personal variability of language areas identified with DCS was observed, despite the similarity of task-specific gamma-band modulated regions across subjects. Post-operative decline in language score was observed in one subject, with resection boundary covering gamma modulated regions during auditory processing tasks but no DCS identified region.

CONCLUSION

Intraoperative language mapping guided by gamma-band ECoG modulations induced by simple word/tone categorization task exhibited similar patterns to more complex naming tasks, suggesting this task may be a viable approach to localize functional cortex, especially in patients unable to reliably perform more difficult paradigms. Utilizing this method in conjunction with DCS mapping guided by visual naming tasks, eloquent cortical language areas may be better preserved reducing post-operative language deficits.
NIMG-69. LEPTOMENINGEAL METASTASES IN IDH-WILDTYPE GLIOBLASTOMAS REVISITED: COMPREHENSIVE ANALYSIS OF INCIDENCE, RISK FACTORS, AND PROGNOSIS BASED ON POSTCONTRAST FLAIR IMAGING
Authors: Park Yae Won , Ahn Sung Soo , Kang Seok-Gu , Chang Jong Hee , Kim Se Hoon
Published: November 2023

BACKGROUND

To comprehensively investigate the incidence, risk factors, and prognosis of leptomeningeal metastases (LM) in isocitrate dehydrogenase (IDH)-wildtype glioblastoma patients.

METHODS

Total 913 IDH-wildtype glioblastoma patients with complete molecular information on IDH mutation and MGMT promoter methylation status were enrolled between 2004 and 2022. LM diagnosis was performed with MRI including postcontrast FLAIR and CSF cytology. Logistic regression analysis for LM development at initial diagnosis and recurrence was performed with clinical, surgical, imaging, and molecular data. The overall survival (OS) was compared between patients with and without LM.

RESULTS

The incidence of LM was 21.8% (199 patients) among patients with IDH-wildtype glioblastoma, with 11.5% (105 patients) at initial diagnosis, and 10.3% (94 patients) at recurrence. Male sex (odds ratio [OR]: 1.74, P = 0.017), MGMT promoter unmethylation (OR: 1.48, P = 0.048), nonlobar location (OR: 2.27, P < 0.001), and presence of necrosis (OR: 3.64, P < 0.001) were independent predictors of LM at initial diagnosis, whereas ventricular opening during surgery (OR: 2.96, P < 0.001) was the only independent predictor of LM at recurrence. The median OS was 16.2 months (interquartile range [IQR]: 9.6-30.4) in patients with LM and 19.3 months (IQR: 12.1-38.5) in patients without LM (log-rank test; P = 0.001).

CONCLUSION

The incidence of LM is high in patients with IDH-wildtype glioblastoma. Aggressive clinical, imaging, and molecular factors are correlated with LM at initial diagnosis, whereas ventricular entry warrant imaging surveillance for LM at recurrence. The prognosis of LM is not discouraging as expected, and promote reconsideration of focused clinical trials.