Despite aggressive treatment, glioblastoma has a poor prognosis due to its infiltrative nature. Spectroscopic MRI-measured brain metabolites, particularly the choline to N-acetylaspartate ratio (Cho/NAA), better characterizes the extent of tumor infiltration. In a previous pilot trial (NCT03137888), brain regions with Cho/NAA ≥ 2x normal were treated with high-dose radiation for newly diagnosed glioblastoma patients. This report is a secondary analysis of that trial where spectroscopic MRI-based biomarkers are evaluated for how they correlate with progression-free and overall survival (PFS/OS). Subgroups were created within the cohort based on pre-radiation treatment (pre-RT) median cutoff volumes of residual enhancement (2.1 cc) and metabolically abnormal volumes used for treatment (19.2 cc). We generated Kaplan–Meier PFS/OS curves and compared these curves via the log-rank test between subgroups. For the subgroups stratified by metabolic abnormality, statistically significant differences were observed for PFS (p = 0.019) and OS (p = 0.020). Stratification by residual enhancement did not lead to observable differences in the OS (p = 0.373) or PFS (p = 0.286) curves. This retrospective analysis shows that patients with lower post-surgical Cho/NAA volumes had significantly superior survival outcomes, while residual enhancement, which guides high-dose radiation in standard treatment, had little significance in PFS/OS. This suggests that the infiltrating, non-enhancing component of glioblastoma is an important factor in patient outcomes and should be treated accordingly.

Introduction: Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)—among other advanced brain tumor imaging modalities—is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI. Methods: Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen’s Kappa. Results: Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects. Conclusions: With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.

Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify early treatment-induced molecular changes that other traditional modalities cannot measure. We developed a pipeline to determine how spectroscopic MRI changes during early RT are associated with patient outcomes to provide insight into the utility of adaptive RT planning. Data were obtained from a study (NCT03137888) where glioblastoma patients received high-dose RT guided by the pre-RT Cho/NAA twice normal (Cho/NAA ≥ 2x) volume, and received spectroscopic MRI scans pre- and mid-RT. Overlap statistics between pre- and mid-RT scans were used to quantify metabolic activity changes after two weeks of RT. Log-rank tests were used to quantify the relationship between imaging metrics and patient overall and progression-free survival (OS/PFS). Patients with lower Jaccard/Dice coefficients had longer PFS (p = 0.045 for both), and patients with lower Jaccard/Dice coefficients had higher OS trending towards significance (p = 0.060 for both). Cho/NAA ≥ 2x volumes changed significantly during early RT, putting healthy tissue at risk of irradiation, and warranting further study into using adaptive RT planning.

Histone deacetylase inhibitors (HDACis) are drugs that target the epigenetic state of cells by modifying the compaction of chromatin through effects on histone acetylation. Gliomas often harbor a mutation of isocitrate dehydrogenase (IDH) 1 or 2 that leads to changes in their epigenetic state presenting a hypermethylator phenotype. We postulated that glioma cells with IDH mutation, due to the presence of epigenetic changes, will show increased sensitivity to HDACis. This hypothesis was tested by expressing mutant IDH1 with a point alteration—converting arginine 132 to histidine—within glioma cell lines that contain wild-type IDH1. Glioma cells engineered to express mutant IDH1 produced D-2-hydroxyglutarate as expected. When assessed for response to the pan-HDACi drug belinostat, mutant IDH1-expressing glioma cells were subjected to more potent inhibition of growth than the corresponding control cells. Increased sensitivity to belinostat correlated with the increased induction of apoptosis. Finally, a phase I trial assessing the addition of belinostat to standard-of-care therapy for newly diagnosed glioblastoma patients included one patient with a mutant IDH1 tumor. This mutant IDH1 tumor appeared to display greater sensitivity to the addition of belinostat than the other cases with wild-type IDH tumors based on both standard magnetic resonance imaging (MRI) and advanced spectroscopic MRI criteria. These data together suggest that IDH mutation status within gliomas may serve as a biomarker of response to HDACis.

Multidisciplinary tumor boards (TB) are an essential part of brain tumor care, but quantifying the impact of imaging on patient management is challenging due to treatment complexity and a lack of quantitative outcome measures. This work uses a structured reporting system for classifying brain tumor MRIs, the brain tumor reporting and data system (BT-RADS), in a TB setting to prospectively assess the impact of imaging review on patient management. Published criteria were used to prospectively assign three separate BT-RADS scores (an initial radiology report, secondary TB presenter review, and TB consensus) to brain MRIs reviewed at an adult brain TB. Clinical recommendations at TB were noted and management changes within 90 days after TB were determined by chart review. In total, 212 MRIs in 130 patients (median age = 57 years) were reviewed. Agreement was 82.2% between report and presenter, 79.0% between report and consensus, and 90.1% between presenter and consensus. Rates of management change increased with increasing BT-RADS scores (0—3.1%, 1a—0%, 1b—66.7%, 2—8.3%, 3a—38.5%, 3b—55.9, 3c—92.0%, and 4—95.6%). Of 184 (86.8%) cases with clinical follow-up within 90 days after the tumor board, 155 (84.2%) of the recommendations were implemented. Structured scoring of MRIs provides a quantitative way to assess rates of agreement interpretation alongside how often management changes are recommended and implemented in a TB setting.

Purpose: Since the prompt recognition of acute pulmonary embolism (PE) and the immediate initiation of treatment can significantly reduce the risk of death, we developed a deep learning (DL)-based application aimed to automatically detect PEs on chest computed tomography angiograms (CTAs) and alert radiologists for an urgent interpretation. Convolutional neural networks (CNNs) were used to design the application. The associated algorithm used a hybrid 3D/2D UNet topology. The training phase was performed on datasets adequately distributed in terms of vendors, patient age, slice thickness, and kVp. The objective of this study was to validate the performance of the algorithm in detecting suspected PEs on CTAs. Methods: The validation dataset included 387 anonymized real-world chest CTAs from multiple clinical sites (228 U.S. cities). The data were acquired on 41 different scanner models from five different scanner makers. The ground truth (presence or absence of PE on CTA images) was established by three independent U.S. board-certified radiologists. Results: The algorithm correctly identified 170 of 186 exams positive for PE (sensitivity 91.4% [95% CI: 86.4–95.0%]) and 184 of 201 exams negative for PE (specificity 91.5% [95% CI: 86.8–95.0%]), leading to an accuracy of 91.5%. False negative cases were either chronic PEs or PEs at the limit of subsegmental arteries and close to partial volume effect artifacts. Most of the false positive findings were due to contrast agent-related fluid artifacts, pulmonary veins, and lymph nodes. Conclusions: The DL-based algorithm has a high degree of diagnostic accuracy with balanced sensitivity and specificity for the detection of PE on CTAs.

PURPOSE/OBJECTIVE(S): Low-dose radiotherapy (LD-RT) is a well-established treatment for multiple human inflammatory conditions. Whole-lung LD-RT may be effective in COVID-19-related pneumonia. MATERIALS/METHODS: Patients hospitalized with COVID-19-related pneumonia receiving supportive care, glucocorticosteroids, and/or remdesivir were administered LD-RT treatment of 0.5 or 1.5 Gy to the bilateral lungs on a prospective, combined phase I/II, multi-site, single-institution trial. Patients were followed for 28 days or until discharge and compared to controls blindly matched by age, comorbidity, duration of symptoms, and disease severity. Eligible patients were confirmed by SARS-CoV-2 positive PCR, unable to wean from oxygen at enrollment, and had radiographic consolidations. Patients were enrolled into 5 cohorts stratified by treatment variables and severity of illness: LD-RT alone vs. LD-RT with concurrent drug therapies, non-intubated vs. intubated status, and low (1.5 Gy) vs. lower (0.5 Gy) radiation dose. Qualitative aims were to establish safety and explore efficacy. Quantitative endpoints were continuous, categorical, and time-to-event, and included clinical recovery, intubation, radiographic changes, and biomarker responses. Intubation endpoints are reported for all cohorts using the log-rank test and Kaplan-Meier method. RESULTS: Outcomes of 80 patients were available for analysis at study closure. In total, 40 of 70 planned patients (57% trial enrollment) received whole-lung LD-RT between April 24 and December 7, 2020 and were compared to 40 matched controls. Cohorts 1&2: Ten non-intubated patients received 1.5 Gy without concurrent COVID-directed drug therapies (10 of 10 planned, 100% cohort enrollment) and were compared to matched controls. Intubation rates were 40% in controls compared to 10% following LD-RT (P = 0.11). Cohort 3: One intubated patient received 1.5 Gy (1 of 20 planned, 5% cohort enrollment). Cohort 4: Twenty separate non-intubated patients received 1.5 Gy with concurrent dexamethasone/remdesivir (20 of 20 planned, 100% cohort enrollment) and were compared to matched controls. Intubation rates were 32% in controls compared to 14% following LD-RT (P = 0.09). Cohort 5: Nine patients received 0.5 Gy with concurrent drug therapies (9 of 20 planned, 45% cohort enrollment) and were compared to matched controls. Zero controls required intubation compared to 11% following LD-RT (P = 0.32). Among all non-intubated patients and matched controls combined (n = 78), mechanical ventilation was required in 28% of controls compared to 12% following LD-RT (reduced 57%, P = 0.05). The trial was prematurely closed due to observed reproducibility of efficacy. A randomized trial is now ongoing. CONCLUSION: In the first, prospective, phase I/II trial of radiotherapy for COVID-19-related pneumonia, a single treatment of whole-lung LD-RT reduced intubation rates by 57% compared to controls in patients receiving supportive care with or without drug therapies (P = 0.05).

Background: Low-dose radiotherapy (LD-RT) has produced anti-inflammatory effects in both animal models and early human trials of COVID-19-related pneumonia. The role of whole-lung LD-RT within existing treatment paradigms merits further study. Methods: A phase II prospective trial studied the addition of LD-RT to standard drug treatments. Hospitalized and oxygen-dependent patients receiving dexamethasone and/or remdesevir were treated with 1.5 Gy whole-lung LD-RT and compared to a blindly-matched contemporaneous control cohort. Results: Of 40 patients evaluated, 20 received drug therapy combined with whole-lung LD-RT and 20 without LD-RT. Intubation rates were 14% with LD-RT compared to 32% without (p = 0.09). Intubation-free survival was 77% vs. 68% (p = 0.17). Biomarkers of inflammation (C-reactive protein, p = 0.02) and cardiac injury (creatine kinase, p < 0.01) declined following LD-RT compared to controls. Mean time febrile was 1.4 vs 3.3 days, respectively (p = 0.14). Significant differences in clinical recovery (7.5 vs. 7 days, p = 0.37) and radiographic improvement (p = 0.72) were not detected. On subset analysis, CRP decline following LD-RT was predictive of recovery without intubation compared to controls (0% vs. 31%, p = 0.04), freedom from prolonged hospitalizations (21+ days) (0% vs. 31%, p = 0.04), and decline in oxygenation burden (56% reduction, p = 0.06). CRP decline following 1st drug therapy was not similarly predictive of outcome in controls (p = 0.36). Conclusions: Adding LD-RT to standard drug treatments reduced biomarkers of inflammation and cardiac injury in COVID-19 patients and may have reduced intubation. Durable CRP decline following LD-RT predicted especially favorable recovery, freedom from intubation, reduction in prolonged hospitalization, and reduced oxygenation burden. A confirmatory randomized trial is now ongoing. Clinical Trial Registration: NCT04366791.

Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60–70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211).

Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Some of the genetic variations identified thus far, such as IDH mutation and MGMT promotor methylation, have implications for survival and response to therapy. A recent analysis of long-term GBM survivors showed that concurrent gain of chromosomes 19 and 20 (19/20 co-gain) is a positive prognostic factor that is independent of IDH mutation status. In this study, we retrospectively identified 18 patients with 19/20 co-gain and compared their imaging features to a control cohort without 19/20 co-gain. Imaging features such as tumor location, size, pial invasion, and ependymal extension were examined manually. When compared without further genetic subclassification, both groups showed similar imaging features except for rates of pial invasion. When each group was subclassified by MGMT promotor methylation status however, the two groups showed different imaging features in a number of additional ways including tumor location, size, and ependymal extension. Our results indicate that different permutations of various genetic mutations that coexist in GBM may interact in unpredictable ways to affect imaging appearance, and that imaging prognostication may be better approached in the context of the global genomic profile rather than individual genetic alterations.