bluuebunny/crossref_metadata_2025 huggingface dataset:
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

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

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

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

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 < 1 yr and 0.78 for OS >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

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

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 (> 6,3 mm for men; > 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 < 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

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

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 < 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 < 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

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.
NIMG-41. ASSOCIATION BETWEEN PERFUSION IMAGING METRICS AND RADIO-PATHOMIC MAPS OF TUMOR PROBABILITY WITHIN AND BEYOND THE CONTRAST-ENHANCING VOLUME IN GLIOMA PATIENTS
Authors: Bobholz Samuel , Lowman Allison , Duenweg Savannah , Winiarz Aleksandra , Stebbins Margaret , Flatley Michael , Nath Biprojit , Kyereme Fitzgerald , Connelly Jennifer , Coss Dylan , Krucoff Max , Banerjee Anjishnu , LaViolette Peter
Published: November 2023

Perfusion MRI, using both contrast-based techniques such as dynamic susceptibility imaging (DSC) and non-contrast-based techniques like arterial spin labeling (ASL) have been used to monitor blood flow as a marker of angiogenic glioma presence, and showed substantial potential in the differentiation of true progression from pseudoprogression post-treatment. This study uses radio-pathomic maps of cellularity sensitive to areas of non-enhancing tumor to test the hypothesis that perfusion-derived markers of tumor probability will associate with tumor presence within contrast-enhancement but not beyond the enhancing margin. This study included pre-surgical relative cerebral blood volume (rCBV) estimates derived from DSC perfusion data from the PENN-GBM dataset (n=456) and presurgical ASL images from the UCSF-PDGM dataset (n=426) for analyses. The T1, T1C, FLAIR, and ADC images from each patient were used to generate radio-pathomic cell density maps using a previously validated model that excels at accurate detection of non-enhancing tumor presence. Mean cell density, rCBV, and ASL were computed for each corresponding patient within included segmentations for contrast-enhancement (excluding necrotic core) and FLAIR hyperintensity (excluding both necrotic core and enhancement). Pearson’s correlations were then used to quantify the association between perfusion-derived estimates and mean cell density within each region of interest. Both rCBV and ASL showed positive associations with cell density within contrast enhancement (rCBV: R=0.280, p< 0.001; ASL: R=0.117, p=0.016). However, both perfusion metrics also showed no association with cell density within the non-enhancing, FLAIR hyperintense region (rCBV: R=0.0162, p=0.731; ASL: R=-0.213, p=0.634). These results suggest that perfusion imaging successfully identifies angiogenic tumor but may be less efficacious in detecting non-enhancing tumor presence. Future studies should examine how perfusion’s relationship with hypercellular tumor presence evolves in the presence of treatment, as well as in relation to other advanced imaging metrics such as MR spectroscopy and CEST imaging.
NIMG-45. EXTERNAL EVALUATION OF A MACHINE LEARNING MODEL EMPLOYING RADIOMICS TO IDENTIFY REGIONS OF LOCAL RECURRENCE IN GLIOBLASTOMA FROM POSTOPERATIVE MRI
Authors: Cepeda Santiago , Luppino Luigi , Wodsinski Marek , Solheim Ole , Perez-Nuñez Angel , Garcia-Garcia Sergio , Karlberg Anna , Eikenes Live , Zamora Tomas , Sarabia Rosario , Arrese Ignacio , Kuttner Samuel
Published: November 2023

The standard surgical goal for operable glioblastomas worldwide is the complete excision of the enhancing tumor. Nevertheless, the peritumoral region harbors infiltrating cells leading to recurrence. Our study aims to evaluate a predictive model designed to predict potential regions of recurrence using voxel-based radiomics analysis on postoperative magnetic resonance imaging (MRI). This retrospective, multi-institutional study involved glioblastoma patients who had undergone complete resection. The training cohort comprised 49 patients from two Spanish institutions, with model evaluation using an external dataset of 27 patients from a Norwegian institution and the public Ivy-Gap dataset. We used follow-up MRI scans for ground truth definition of recurrence, while postoperative multiparametric MRI scans provided the data for extracting voxel-based radiomic features. Our method employed an unsupervised, hybrid approach, which combined a deep neural network and instance optimization, to align the MRI sequences for each patient, registering the follow-up with the postoperative scans. To generate ground truth labels, we segmented the peritumoral region in the postoperative scans, identified as the area showing T2/FLAIR signal alterations, in addition to the enhancing tumor visible in the registered follow-up scan. Overlapping voxels between the peritumoral and enhancing tumor regions were classified as recurrence, while non-overlapping voxels were labeled as nonrecurrence. Radiomic features were subsequently extracted from the postoperative peritumoral region. We trained four machine learning classifiers to predict recurrence. Among these, the Categorical Boosting (CatBoost) classifier demonstrated excellent performance on the test dataset, achieving an average area under the curve (AUC) of 0.83 ± 0.07, and an accuracy of 0.80 ± 0.12, based on voxel-wise comparison with the ground truth. Our study resulted in a method that accurately predicts the area of future tumor recurrence in glioblastoma patients' MRI scans. This innovation could potentially tailor surgical and radiotherapy treatment strategies to these specific areas, possibly extending patient survival.
NIMG-48. ASSOCIATIONS BETWEEN HETEROGENEITY OBSERVED IN O-6-METHYLGUANINE-DNA METHYLTRANSFERASE (MGMT) ASSAY MEASUREMENTS AND MGMT-BASED IMAGING SIGNATURE BASED ON MRI AND DEEP LEARNING
Authors: Saxena Sanjay , Kazerooni Anahita Fathi , Toorens Erik , Bakas Spyridon , Akbari Hamed , Mamourian Elizabeth , Ganguly Tapan , Nasrallah MacLean P , Davatzikos Christos
Published: November 2023

BACKGROUND

O-6-methylguanine-DNA methyltransferase(MGMT), a gene promoter, corresponds with the efficacy of standard therapy for Glioblastoma (GBM) patients. If a single sample is sequenced, an appropriate diagnosis of MGMT methylation may be hampered by intratumoral heterogeneity. This work proposes a non-invasive in-vivo estimation of MGMT methylation using deep learning and multi-parametric MRI (mpMRI). Further, it quantifies spatial heterogeneity and establishes the associations between MGMT assay measurement and MGMT imaging signature heterogeneity.

METHODS

For this study, mpMRI structural scans (T1, T2, FLAIR and T1-Gd) of 498 newly diagnosed GBM patients were considered. These patients underwent surgical tumor resection, and MGMT methylation testing was retrospectively collected. By overlaying local and regional 2D patches of size 32 X 32 over the whole tumor on mpMRI scans, a 10-fold cross-validated deep convolutional neural network model was trained considering five layers on the discovery cohort (n=458). The trained model was applied to an independent multi-sample cohort (n=40) to compute the MGMT methylation at the pixel level for imaging-derived maps generation and heterogeneity quantification. The independent cohort included the patients for whom multiple tissue specimens were sequenced for MGMT methylation.

RESULTS

The patch-based deep model produced an area under the ROC curve of 0.76 (95% CI: 0.71–0.82) for MGMT status prediction. This model showed a strong association between homogeneously MGMT methylated and heterogeneous cases with MGMT Assay measurement of multiple samples with Pearson’s correlation coefficients of 0.64 (p < 0.05) and 0.78 (p < 0.01), respectively. Further, heterogeneity with a significantly higher variance was also observed in heterogeneous cases in developed MGMT imaging signature.

CONCLUSION

The proposed model efficiently determines MGMT promoter methylation and quantifies GBM spatial heterogeneity non-invasively. Also, it showed a significant association between the heterogeneity observed in MGMT-based imaging signature and MGMT assay measurements.
NIMG-53. IMAGING FEATURES AND CONSIDERATION OF PROGRESSION PATTERN OF DIFFUSE HEMISPHERIC GLIOMAS, H3 G34-MUTANT
Authors: Kibe Yuji , Ohka Fumiharu , Motomura Kazuya , Aoki Kosuke , Maeda Sachi , Yamaguchi Junya , Shimizu Hiroki , Saito Ryuta
Published: November 2023

BACKGROUND

Diffuse hemispheric gliomas, H3 G34-mutant (DHGs-G34m) are newly recognized pediatric-type diffuse high-grade gliomas. We describe detail imaging features of seven cases of DHGs-G34m and consider about progression pattern of DHGs-G34m.

RESULTS

H3 G34R or H3 G34V was detected by sanger sequencing in all tumors. Mean age of onset was 16.5 years (range: 10-26). Tumors were located on frontal (2), parietal (2), temporal lobe (1) and insular cortex (1), respectively. In one case, gliomatosis cerebri-like multiple lesions involving the cortex and basal ganglia occurred. Magnetic resonance imaging showed T2/FLAIR high lesions with poor contrast enhancement in all cases. All tumors harbored restriction of diffusion. Cystic component and hemorrhage were observed in five and three cases, respectively. Six patients underwent preoperative positron emission tomography. Strong accumulation of methionine and partial accumulation of FDG in all cases. All tumors harbored T2/FLAIR high lesions in the deep white matter, most of which showed methionine accumulation. All patients underwent surgery (total resection in one case, partial resection in five cases, and biopsy in one case) followed by radiation chemotherapy. The mean progression free survival was 9.9 months (range: 1.6-33.1 months). All tumors harbored diffuse infiltration along the white matter, which was temporarily reduced by bevacizumab, but eventually invaded into cerebral peduncle via pyramidal tract and into contralateral brain via corpus callosum or anterior commissure in six cases. Extensive infiltration of tumor cells into the contralateral brain and brain stem was confirmed histopathologically in the autopsy brain of one case. The mean overall survival was 21.6 months (range: 8.9-48.3 months).

CONCLUSION

DHGs-G34m showed deep white matter infiltration from the time of initial onset, which made gross total resection difficult. Residual lesions extensively infiltrated along the white matter and eventually invaded the brainstem and contralateral brain, leading to death.
NIMG-54. CONFOCAL FLUORESCENCE ENDOMICROSCOPY: A PROSPECTIVE MULTI-CENTERED, ASSESSOR BLINDED PILOT STUDY FOR THE DIAGNOSIS OF BRAIN TUMORS
Authors: Byun Yoon Hwan , Won Jae-Kyung , Hong Duk Hyun , Kang Ho , Kim Jang Hun , Yu Mi Ok , Kim Min-Sung , Kim Yong-Hwy , Park Kyung-Jae , Jeong Min-Jae , Hwang Kyungmin , Kong Doo-Sik , Park Chul-Kee , Kang Shin-Hyuk
Published: November 2023

Frozen section analysis remains the gold standard for intraoperative diagnosis during brain tumor surgeries; however, it is associated with extensive time consumption and the potential for freezing artifacts. In recent years, confocal laser endomicroscopy (CLE) has been actively studied as a promising alternative to address these limitations of frozen section analysis. In this prospective, multi-centered, assessor-blinded pilot study, our aim was to evaluate the diagnostic effectiveness of cCeLL - Ex vivo, a second-generation CLE model, compared to frozen section analysis for brain tumor diagnosis. We enrolled a total of 55 patients with newly diagnosed brain tumors between October 2022 and December 2022. Biopsy samples were obtained during surgical resection, and each tissue sample was divided into three smaller samples for permanent section analysis, frozen section analysis, and imaging acquisition using cCeLL - Ex vivo. The efficacy of both frozen section analysis and cCeLL - Ex vivo was assessed by comparing their diagnoses to the results from permanent section analysis. The diagnostic accuracy of cCeLL - Ex vivo was slightly higher than that of frozen section analysis, with accuracies of 89.2% and 86.5%, respectively. Both methods demonstrated a sensitivity of 92.2%. Notably, cCeLL - Ex vivo exhibited a higher specificity of 70% compared to frozen section analysis, which had a specificity of 50%. Additionally, the mean time from sample preparation to diagnosis was significantly shorter in cCeLL - Ex vivo (13 min 17 sec) compared to frozen section analysis (28 min 28 sec). These results indicate the promising potential of cCeLL - Ex vivo as a complementary tool for intraoperative diagnosis of brain tumors. Future studies are expected to provide more evidence regarding the potential clinical utility of CLEs in clinical settings.
NIMG-55. PREDICTING SITES OF TUMOR PROGRESSION IN THE INVASIVE MARGIN OF GLIOBLASTOMAS (PRAM-GBM STUDY): AN INTERIM ANALYSIS OF A MULTI-CENTER IMAGING BIOMARKER STUDY
Authors: Price Stephen , Mayrand Roxanne , Wan Yizhou , Cream Lynn , Cook Julia , Dayimu Alimu , Jenkinson Michael , Varma Anil , Ashkan Keyoumars , Thomson Simon , Smith Stuart , Demiris Nikolaos , Matys Tomasz , Li Chao
Published: November 2023

INTRODUCTION

Although glioblastoma cells extend throughout the brain, virtually all patients die from local progressive disease. This progressive tumor occurs at the resection margins and usually within the high-dose radiotherapy field. If we could identify where the tumor would progress, we could consider personalizing radiotherapy and surgical targets. Previous work has shown diffusion tensor MR as a potential biomarker of occult invasion. Biopsy studies reveal that the q-anisotropic component correlates with high-density tumor, and the extent of resection correlates with improved survival. We hypothesize that this is a biomarker that can predict where glioblastomas may progress. STUDY DESIGN: A multicentre, pragmatic, longitudinal observational cohort study from 6 centers. This is a planned interim analysis of the first cohort.

METHODS

Patients with glioblastomas suitable for maximal resection were imaged pre-operatively with a diffusion tensor MRI protocol. This was processed using a tensor decomposition method to generate the q-anisotropic component. Masks of the abnormal q-component were overlaid on the masks of new areas of contrast enhancement at progression (ground truth). Intersecting voxels were classified as true positive, true negative, false positive, and false negative, and the sensitivity and specificity were calculated.

RESULTS

139 patients were recruited, but 50 were withdrawn. The interim analysis was planned for the first 2/3rds of the cohort (55 patients). Combining q and contrast enhancement provided the best predictor of site of tumor progression with a mean sensitivity of 79% [95%CI: 71-88%] compared to contrast enhancement of only 50% [95%CI: 39-61%]. Specificity remained high in both groups (CE+q mean 94% [95%CI: 93-95%] vs. CE alone 98% [95%CI: 97-98%]).

CONCLUSION

The anisotropic diffusion component, q, provides the best biomarker for identifying ‘residual tumor.’ This biomarker will form the basis of an early phase surgical trial IDEAL Stage 1 and 2a study to change surgical resection target.
NIMG-60. PATTERNS OF PROGRESSION IN GLIOBLASTOMA PATIENTS UNDERGOING IMMUNE CHECKPOINT INHIBITOR THERAPY
Authors: Rochand Adrien , Baldini Capucine , Touat Mehdi
Published: November 2023

Glioblastoma (GBM) is the most common primary brain neoplasm with a median survival of 15 months. This retrospective study investigated the patterns of radiologic progression in GBM patients treated with immune checkpoint inhibitors (ICI). Among 16 patients, PseudoProgression (PsPD) was observed in 43% and Hyperprogression (HPD) in 19% of cases. Patients with PsPD had an overall survival of 17.6 months versus 2.9 months for HPD. Identifying these atypical responses early is crucial for optimizing treatment strategies and patient selection. Further research is needed to identify prognostic indicators and biomarkers for immunotherapy efficacy in GBM.
NIMG-62. QUANTITATIVE ASSESSMENT OF T2-FLAIR MISMATCH IN HUMAN NON-ENHANCING GLIOMAS USING SUBTRACTION MAPS OF T2-W AND FLAIR MRI
Authors: Cho Nicholas , Sanvito Francesco , Le Vien , Oshima Sonoko , Teraishi Ashley , Yao Jingwen , Raymond Catalina , Pope Whitney , Nghiemphu Phioanh , Lai Albert , Cloughesy Timothy , Salamon Noriko , Ellingson Benjamin
Published: November 2023

INTRODUCTION

The T2-FLAIR mismatch (T2FM) sign on anatomical MRI is highly specific for isocitrate dehydrogenase (IDH)-mutant 1p/19q-intact gliomas (astrocytomas) and is characterized by relative hypointense FLAIR signal within the T2 hyperintense lesion. However, studies on T2FM sign have mostly utilized qualitative visual assessment. This study explored quantitative subtraction maps of T2-w and FLAIR MRI in human non-enhancing gliomas to quantify the extent of T2FM and assess T2FM subregion volumetric and diffusion MRI differences.

METHODS

Seventy-two newly-diagnosed, non-enhancing gliomas with known IDH- and 1p/19q-status from The Cancer Imaging Archive (TCIA) were studied. An institutional cohort (n= 36) was analyzed for validation. T2-FLAIR subtraction maps were generated from voxel-wise subtraction of co-registered, normalized T2-w and FLAIR MRI scans. Tumor volumes of interest (VOIs) were segmented on the T2 hyperintensity excluding macroscopic cysts. Tumor VOIs were split into mismatched and non-mismatched subregions using consistent T2-FLAIR subtraction map thresholds. Tumor subregion volumes and normalized apparent diffusion coefficient (nADC) values were obtained, and tumor T2FM percentage was calculated.

RESULTS

In the TCIA cohort, a threshold of > 16% T2FM had 92.3% specificity and 34.8% sensitivity and a threshold of > 42% T2FM had 100% specificity and 21.7% sensitivity for classifying IDH-mutant astrocytomas (AUC= 0.704, P= 0.004). IDH-mutant astrocytomas with > 16% T2FM had higher nADC in mismatched compared to non-mismatched subregions (mean difference= 0.51; P< 0.0001). Using the same T2FM thresholds, these findings were validated in the institutional cohort for glioma classification (AUC= 0.918, P< 0.0001; > 16% T2FM: 100% specificity, 66.7% sensitivity, PPV= 100%, NPV= 65.2%; > 42% T2FM: 100% specificity, 23.8% sensitivity, PPV= 100%, NPV= 48.3%) and subregion nADC differences (mean difference= 0.56, P< 0.0001).

CONCLUSIONS

T2-FLAIR subtraction maps may be a useful, automated tool for classifying non-enhancing gliomas and exploring T2FM subregion differences. Elevated nADC in mismatched subregions may reflect microcystic changes.
NIMG-64. IN VIVO METABOLIC PROFILING FOR RECURRENT GLIOMA
Authors: Li Yan , Lafontaine Marisa , Autry Adam , Jiang Fei , Shai Anny , Phillips Joanna , Chang Susan
Published: November 2023

INTRODUCTION

The 2021 WHO classification has identified the importance of molecular features in diagnosing adult glioma. The goal of this study was to use short echo MR spectroscopic imaging (MRSI) to evaluate the metabolite profiles at recurrence and characterize in vivo metabolism in relation to pathology by combining it with image-guided tissue samples.

METHODS

Fifty-one patients with an initial diagnosis of glioma (18 astrocytoma, 14 oligodendroglioma, and 19 glioblastoma) received MR examinations before surgical resection of progressive disease confirmed histologically. The 3D MRSI data were combined, processed, and quantified by LCModel with a simulated basis set. Metabolite levels were compared between contrast-enhancing lesions (CEL), non-enhancing lesions (NEL), and patient groups. Spectra data centered at the tissue target location were correlated to pathological parameters from the samples (0-4 samples/subject).

RESULTS

74.5% (38/51) patients had enhancing tumors, with median CEL volume of 4.2 cm3 (min-max: 0.2-28.5 cm3) and median NEL volumes of 50.6 cm3 (4.8-167.2 cm3). The patients with GBM had significantly larger CEL volumes than the others (p=0.009).18/29 (62%) patients with lower-grade glioma had malignant progression to higher grades. Those who progressed from grade 2 to 3 or 4 had higher myo-inositol/choline (mean±SD, 2.62±0.64, N=18) compared to those who recurred as grade 2 (1.88±0.52, N=5, p = 0.015). Of the 51 patients, 40/65 in vivo spectra voxels centered where the tissues were sampled displayed good quality, with 27 having active tumors, 7 having treatment effects, and 6 having mixed tumors/treatment effects. The levels of choline/creatine and myo-inositol+glycline/creatine were significantly correlated with MIB-1 (p< 0.0001, =0.034; r=0.563, 0.349), but no difference was found between the locations with active tumors and treatment effects. DISCUSSION: This study demonstrated metabolite variations at the recurrence. Ongoing studies will further characterize the metabolite profiles for malignant progression and differences between active tumors and treatment effects.
NIMG-65. METHYLTHIOADENOSINE PHOSPHORYLASE STATUS CORRELATES WITH CLINICAL OUTCOME AND11C-METHIONINE UPTAKE IN ASTROCYTOMA, IDH-MUTANT
Authors: Yamamura Toshihiro , Tamura Kaoru , Kobayashi Daisuke , Inaji Motoki , Toyama Yuka , Hara Shoko , Tanaka Yoji , Nariai Tadashi , Kiyokawa Juri , Ishii Kenji , Maehara Taketoshi
Published: November 2023

PURPOSE

Methylthioadenosine phosphorylase (MTAP) immuno histochemistry staining has been proposed as a surrogate of Cyclin-dependent kinase inhibitor 2A homozygous deletion (CDKN2A HD) in various types of tumors. This study was designed to determine whether MTAP status correlates with clinical outcome and uptake of 11C-methionine in astrocytoma, IDH-mutant.

METHODS

We conducted a MTAP immunohistochemistry staining of 30 astrocytoma, IDH-mutant patients who underwent 11C-methionine positron emission tomography scans prior to surgical resection from 2000 to 2020. The tumor-to-normal (T/N) ratio of 11C-methionine uptake was calculated by dividing the mean standardized uptake value (SUV) for the tumor by the mean SUV of the normal brain.

RESULTS

Eight (26.7%) of the thirty astrocytoma, IDH-mutant patients exhibited loss of cytoplasmic MTAP expression, which is accompanied with a poor prognosis. The median progression free survival (PFS) in astrocytoma, IDH-mutant patients with loss of MTAP was 1.88 years and significantly shorter than that of those with MTAP retention (6.80 years, p = 0.003). The median Overall survival in astrocytoma, IDH-mutant patients with loss of MTAP was 5.23 years, again significantly shorter than that of those with MTAP retention (10.69 years, p = 0.0191). Multivariate analysis revealed that MTAP status was an independent prognostic marker for PFS in astrocytoma, IDH-mutant patients. The median T/N ratio in tumors with loss of cytoplasmic MTAP expression was 2.12 (IQR 1.92-2.50), i.e., significantly higher than that of tumors with MTAP retention (1.65, IQR 1.23-1.94, p = 0.0116, U test). Thirteen (59.1%) of twenty-two patients with MTAP retention recurred and nine patients underwent a second surgery after radiation treatment with or without chemotherapy. Three (33.3%) of the nine recurrent patients showed loss of MTAP immunoreactivity, suggesting a role for this loss in tumor progression.

CONCLUSION

Our study showed MTAP status to correlate with clinical outcome and T/N ratio of 11C-methionine in astrocytoma, IDH-mutant patients.
NIMG-66. RADIOGENOMICS-BASED HETEROGENEITY ANALYSIS OF GLIOBLASTOMA REVEALS MR IMAGING PHENOTYPICAL CHARACTERIZATION OF EGFR MUTATIONS
Authors: Yu Fanyang , Guo Jun , Kazerooni Anahita Fathi , Akbari Hamed , Toorens Erik , Sako Chiharu , Mamourian Elizabeth , Bagley Stephen J , Binder Zev , Lustig Robert A , Brem Steven , O'Rourke Donald M , Ganguly Tapan , Bakas Spyridon , Nasrallah MacLean P , Chaudhari Pratik , Davatzikos Christos
Published: November 2023

PURPOSE

EGFR is one of the most frequently altered genes in glioblastoma, while also being an attractive therapeutic target for treatment. Having in vivo, imaging-based markers of EGFR mutations, and as well as characterizing molecular heterogeneity, are important for patient management and stratification into trials. Toward this end, we present deep learning models of imaging signatures of EGFR mutations built from MRI.

METHODS

Our cohort consists of 286 glioblastoma patients with multi-parametric MRI (mpMRI) scans (T1, T1-Gd, T2, T2-FLAIR, DSC, DTI). Radiomics features, including histograms, morphologic and textural descriptors, were first derived. Genomic information was determined from a targeted next generation sequencing (NGS) panel. We jointly trained a variational auto-encoder and a multi-label classifier for predicting 4 key driver genes EGFR, NF1, PTEN, TP53 to learn a latent representation reflecting the molecular heterogeneity in the dataset. The latent representation was analyzed using principal component analysis (PCA). We calculated the Euclidean distance between imaging features of tumors with EGFR plus 1 of the other 3 mutations, from those of tumors having only EGFR mutations. We also analyzed the imaging signatures and variant allele frequencies (VAFs) of individuals with multiple (typically 3-4) resected tissue samples (n=49).

RESULTS

Co-occurrence of mutations in any of NF1, PTEN, TP53 genes with EGFR mutations resulted into dominance of imaging signatures of these other mutations over that of EGFR mutations. Interestingly, tumors with homogeneously high VAFs in EGFR mutations (n=3) exhibit strong phenotypical difference from the exclusive EGFR mutated group, while individuals with heterogeneous EGFR mutations (n=4) do not show such differences.

CONCLUSION

Our preliminary findings suggest EGFR imaging characteristics can be dominated by those of other co-occurring mutations. Tumors with homogeneously high VAFs, potentially indicating presence of germline EGFR mutations, lead to relatively distinct imaging phenotypes.