Citations

Abstract Background : Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences. Methods : Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients (299 males and 195 females). Results : Among males, tumor (T1Gd) radius was a predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, p<0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p=0.010 t-test), but tumor size was not correlated with female overall survival (p=0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p=0.004, F p=0.001, t-test). Conclusion : Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes.

The NCCN Guidelines for Non–Small Cell Lung Cancer (NSCLC) address all aspects of management for NSCLC. These NCCN Guidelines Insights focus on recent updates in immunotherapy. For the 2020 update, all of the systemic therapy regimens have been categorized using a new preference stratification system; certain regimens are now recommended as “preferred interventions,” whereas others are categorized as either “other recommended interventions” or “useful under certain circumstances.”

Abstract We report a case of an adult male patient with multifocal urinary bladder paragangliomas, which were negative on 68Ga-DOTATATE PET/CT scan, but positive on 123I-MIBG SPECT/CT scan. While the 68Ga-DOTA analog PET/CT exhibits superior performance in diagnosis and staging of pheochromocytoma and paraganglioma, our case demonstrates negative somatostatin receptor expression in this rare entity and indicates that 123I-MIBG SPECT/CT still plays a vital role in characterization of bladder paraganglioma.

Abstract INTRODUCTION Neuroimaging dogma for glioblastoma asserts that hyperintensity on T1Gd MRI reveals the bulk of the tumor, while T2/FLAIR signal indicates edema. However, it is unclear whether this edema results from immune response or increased tumor cells. Further, one significant driver of the known sex differences in glioblastoma may be differences in immune response, due to the X-linkage of many immune genes. Based on this, we hypothesized that assumptions regarding tumor cellularity in T2/FLAIR images should be tailored to the biological sex of the patient. METHODS Using a retrospective cohort of 18 primary glioblastoma patients receiving multiple image-localized biopsies (82 total) and standard MRI, we assessed: distance of biopsy from T1Gd and T2 areas; a pathologist’s score of percent tumor cell density; and an imaging-based invasion metric, D/ρ. This metric is derived from the biomathematical Proliferation-Invasion model of glioma growth, which features two parameters, net growth rate (ρ) and net invasion rate (D). Their ratio D/ρ is related to degree of invasion, and is estimated from volumetric measurements of MRI abnormalities. Additionally, 25 patient-derived xenograft models implanted in females were grown until moribund, at which point brains were excised and stained for DAPI (to show all cells) and Lamin (to highlight tumor cells). Image processing of lamin-stained sections defines contours of intensity correlating with cell density. RESULTS Outside both the T1Gd and T2 region, male patient biopsies had higher tumor cell densities than females. Males also tended to have higher invasion metrics. Although each set derived from different patients, preclinical metrics of invasion were positively correlated with clinical invasion in females but negatively correlated in males. CONCLUSION Our preliminary finding that cell distribution patterns correlate with imaging metrics differently between the sexes supports the hypothesis that the degree of tumor cell density represented on certain MRI sequences may be sex-specific.

Abstract INTRODUCTION Locations of gliomas may influence clinical presentations, molecular profiles, treatment options, and prognoses. Using the Mayo Clinic Arizona Cancer Center registry, we analyzed the frequency at which gliomas were identified in different regions of the brain. We evaluated molecular profiles, clinical courses and survival by anatomic location. METHODS Registry was queried to include patients with glioma over a 10-year period. Statistical analyses were used to compare demographic, genetic, and clinical characteristics among patients with gliomas in different locations. RESULTS 182 gliomas were identified. Of the tumors confined to a single lobe, there were 51 frontal (28.0%), 50 temporal (27.5%), 22 parietal (12.1%), and 7 occipital tumors (3.8%) identified. Multifocal disease was noted in 38 patients (20.9%). Tumors affecting temporal lobe were associated with reduced overall survival when compared to all other tumors (11.0 months vs. 13.0 months, log-rank p=0.0068). However, this disparity became insignificant when adjusted for tumor grade, age, and surgical approach [HR(95% CI) 1.26(0.87, 1.82), p=0.212]. Out of 82 cases tested for IDH-1, 10 were mutated (5.5%). IDH-1 mutation was present in 6 frontal, 2 temporal, 1 thalamic, and 1 multifocal tumor. Out of 21 cases tested for 1p19q deletions, 12 were co-deleted, 9 of which were frontal lobe tumors. MGMT methylation was assessed in 45 cases; 7 of 14 frontal tumors and 6 of 13 temporal tumors were methylated. ATRX loss was detected in 2/42 assessed cases. CONCLUSION Our results support the hypothesis that the anatomical locations of gliomas influence patients’ clinical courses. Tumors involving the temporal lobe were associated with poorer survival, though this association appeared to be driven by these patients’ more aggressive tumor profiles and higher risk baseline demographics. Molecular analysis was limited by low prevalence of genetic testing in the study sample, highlighting the importance of capturing this information for all gliomas.

Abstract Glioblastoma (GBM) is the most aggressive primary brain tumor with a median overall survival of 15 months with standard-of-care treatment. GBM patients sometimes present with a cystic component, which can be identified through magnetic resonance imaging (MRI). Previous studies suggest that cysts occur in 7–22% of GBM patients and have reported mixed results regarding whether cystic GBM have a survival benefit compared to noncystic GBM. Using our large retrospective cohort of 493 first-diagnosis GBM patients, we aim to elucidate this link between cystic GBM and survival. Within this cohort, 88 patients had a significant cystic component at presentation as identified on MRI. Compared to noncystic GBM (n=405), cystic GBM patients had significantly better overall survival (15 vs 22 months median, log-rank, p=0.001) and were significantly younger at the time of presentation (t-test, p=0.002). However, within patients that received current standard-of-care treatment (n=184), cystic GBM (n=40) was not as beneficial for outcome (22 vs 25 months, log-rank, p=0.3). We also did not observe a significant survival benefit when comparing this standard-of-care cystic cohort to cystic GBM patients diagnosed before the standard was established (n=19, 25 vs 23 months, log-rank, p=0.3), but the analogous result for noncystic GBM patients gives a sizeable benefit, as expected (n=144, n=111, respectively, 22 vs 12 months, log-rank p < 0.0001). Together, these results on current standard-of-care may explain later studies that note no significant survival benefit for cystic GBM patients receiving current standard-of-care. We also report differences in the absolute and relative sizes of imaging abnormalities on MRI and in prognostic impact of cysts based on sex. We discuss current hypotheses for these observed differences, including the possibility that the presence of a cyst could be indicative of a less aggressive tumor.

Abstract There have been increasing efforts to standardize MRI scanning protocols for both routine and clinical trial imaging of glioma. The recent BTIP guidelines propose acquisition of T2-weighted images after gadiolinium (Gd) based contrast injection and before post-contrast 3D T1-weighted (T1W) images to control timing of images after contrast administration. While Gd-contrast shortens T1W signal and appears hyperintense on magnetic resonance imaging (MRI), Gd-contrast also shortens T2W signal, which could result in unintended alternations in T2W signal intensities. This has potential implications for model-based approaches for GBM diagnosis and the differential diagnosis of other tumor types (e.g., lymphoma) that rely on T2W signal characteristics. To our knowledge, no neuroimaging studies have formally evaluated the impact of Gd contrast on T2W imaging. We acquired multi-echo T2 sequences (TE=14, 28, 41, 55, 69 ms) both prior to and after the administration of Gd for 5 patients suspected of having a brain tumor. Quantitative T2 maps were created by fitting the signal decay to a signal exponential with the Levenburg-Marqurdt algorithm. Percent difference maps were calculated to compare the quantitative T2 changes between the pre- and post-Gd T2 maps. Additionally, we performed a Wilcoxon Rank-Sum test comparing T2 values within regions of interest (ROIs) representing the tumor and normal appearing white matter (NAWM). Significant differences between the T2 values in the tumor and NAWM ROIs were seen for 4 and 3 of the patients, respectively (all p-values < 0.01). Our initial data suggests that the administration of Gd contrast may affect T2 values in both the tumor and NAWM, which could impact quantitative image-based models and diagnoses in glioma. We are currently replicating these preliminary results in an expanded cohort.

Abstract Determining effective therapies for patients with recurrent glioblastoma remains difficult especially in small early phase clinical trials. Currently utilized estimators of treatment response rely on two-dimensional measurements of tumor progression (e.g. RANO, RECIST, MacDonald) that have often fallen short in reliably connecting patients who respond with positive survival outcomes. This has prompted consideration of advanced imaging and volumetric measurements by the RANO working group and others. Our proposed approach, Days Gained (DG), uses volumetric measurements to calculate a personalized response metric based on change in tumor growth characteristics pre/post-treatment. DG has shown promise for connecting imageable treatment response with clinically meaningful (statistically significant) survival benefit when applied in upfront and recurrent therapy settings, even in the context of coincident bevacizumab treatment. In this study, we seek to consider a new cohort of patients receiving bevacizumab in combination with other novel therapies to distinguish any subpopulation of patients with meaningful response. In this work, we identified a subset of 16 patients from bevacizumab clinical trials with data available for DG analysis requiring serial imaging (T1Gd and FLAIR) prior to and after the first cycle of therapy. Each trial evaluated bevacizumab alone versus bevacizumab plus either dasatinib or TRC105 in recurrent disease. Discrimination of time to progression (TTP) was evaluated at DG thresholds identified from our prior analysis of patients treated with bevacizumab. Using previously identified DG thresholds for clinically significant treatment benefit, in our cohort, DG measured by serial FLAIR imaging was significant in predicting longer TTP (120 DG, p=0.014), but T1Gd DG scores did not attain significance (p=0.630). Given the limited insights in connecting response metrics to accurately predicted outcomes, these data further support the use of DG as a burgeoning marker of treatment response (or lack of response) that may be useful for more routine integration into clinical trials.

Abstract BACKGROUND Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care. METHODS A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image features trained and cross-validated to predict FPKM values of CD68, CASP3, CD8A and IL13RA2. Training data included RNAseq from 38 image-localized biopsies from 15 newly-diagnosed GBM patients. These models were then applied to two independent patients, chosen based on therapy and the quality of image registration, at three different time points, just prior to receiving IL13RA2 targeted CAR-T therapy for rGBM, after 2 cycles and after 4 cycles, resulting in a voxel-based prediction of the relative expression levels of these genes. RESULTS Cross-validation of the proposed machine learning models demonstrated a Pearson Correlation coefficient between predicted and observed FPKM values of 0.89 (CD68), 0.92 (CASP3), 0.93 (CD8A), and 0.88 (IL13RA2). When the models were applied to the two CAR-T patients, CD68-modeled expression levels were seen to increase throughout therapy for one patient, while remaining stable for the other. Survival from first CAR-T infusion was, respectively, 412 and 83 days suggesting that the increased CD68 was indicative of therapeutic effectivity. Further, the spatial activity predictions were consistent with expected therapeutic action as the correlation coefficient between CASP3 and the product of IL13R2 and CD8A expression was 0.81, suggesting the T-cells targeting IL13RA2 were inducing cell death. CONCLUSIONS Preliminary results with our model highlights the potential of spatially resolved radiomic maps to provide insight into regional therapeutic effectivity.