Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning

PURPOSE

High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care.

METHODS

Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70).

RESULTS

The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor.

CONCLUSION

The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

Data-driven decomposition and staging of flortaucipir uptake in Alzheimer's disease

INTRODUCTION

Previous approaches pursuing in vivo staging of tau pathology in Alzheimer's disease (AD) have typically relied on neuropathologically defined criteria. In using predefined systems, these studies may miss spatial deposition patterns which are informative of disease progression.

METHODS

We selected discovery (n = 418) and replication (n = 132) cohorts with flortaucipir imaging. Non-negative matrix factorization (NMF) was applied to learn tau covariance patterns and develop a tau staging system. Flortaucipir components were also validated by comparison with amyloid burden, gray matter loss, and the expression of AD-related genes.

RESULTS

We found eight flortaucipir covariance patterns which were reproducible and overlapped with relevant gene expression maps. Tau stages were associated with AD severity as indexed by dementia status and neuropsychological performance. Comparisons of flortaucipir uptake with amyloid and atrophy also supported our model of tau progression.

DISCUSSION

Data-driven decomposition of flortaucipir uptake provides a novel framework for tau staging which complements existing systems.

HIGHLIGHTS

NMF reveals patterns of tau deposition in AD. Data-driven staging of flortaucipir tracks AD severity. Learned flortaucipir patterns overlap with AD-related gene expression.

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.

Patterns of Glucose Metabolism in [ 18 F]FDG PET Indicate Regional Variability and Neurodegeneration in the Progression of Alzheimer's Dementia

In disorders of cognitive impairment, such as Alzheimer's disease, neurodegeneration is the final common pathway of disease progression. Modulating, reversing, or preventing disease progression is a clinical imperative most likely to succeed following accurate and explanatory understanding of neurodegeneration, requiring enhanced consistency with quantitative measurements and expanded interpretability of complex data. The on-going study of neurodegeneration has robustly demonstrated the advantages of accumulating large amounts of clinical data that include neuroimaging, motiving multi-center studies such as the Alzheimer's Disease Neuroimaging Initiative (ADNI). Demonstrative advantages also arise from highly multivariate analysis methods, and this work reports advances provided by non-negative matrix factorization (NMF). NMF revealed patterns of covariance for glucose metabolism, estimated by positron emission tomography of [ 18 F]fluorodeoxyglucose, in 243 healthy normal participants of ADNI. Patterns for glucose metabolism provided cross-sectional inferences for 860 total participants of ADNI with and without cerebral amyloidosis and clinical dementia ratings (CDR) ranging 0-3. Patterns for glucose metabolism were distinct in number and topography from patterns identified in previous studies of structural MRI. They were also distinct from well-establish topographies of resting-state neuronal networks mapped by functional magnetic resonance imaging. Patterns for glucose metabolism identified significant topographical landmarks relating age, sex, APOE ε4 alleles, amyloidosis, CDR, and neurodegeneration. Patterns involving insular and orbitofrontal cortices, as well as midline regions of frontal and parietal lobes demonstrated the greatest neurodegeneration with progressive Alzheimer's dementia. A single pattern for the lateral parietal and posterior superior temporal cortices demonstrated preserved glucose metabolism for all diagnostic groups, including Alzheimer's dementia. Patterns correlated significantly with topical terms from the Neurosynth platform, thereby providing semantic representations for patterns such as attention, memory, language, fear/reward, movement and motor planning. In summary, NMF is a data-driven, principled, supervised statistical learning method that provides interpretable patterns of neurodegeneration. These patterns can help inform the understanding and treatment of Alzheimer's disease.

Highlights

▪ Data-driven non-negative matrix factorization (NMF) identified 24 canonical patterns of spatial covariance of cerebral glucose metabolism. The training data comprised healthy older participants (CDR = 0 without amyloidosis) cross-sectionally drawn from ADNI. ▪ In healthy participants, mean SUVRs for specific patterns in precuneus, lateral parietal cortex, and subcortical areas including superficial white matter and striatum, demonstrated increasing glucose metabolism with advancing age. ▪ In asymptomatic participants with amyloidosis , glucose metabolism increased compared to those who were asymptomatic without amyloid , particularly in medial prefrontal cortex, frontoparietal cortex, occipital white, and posterior cerebellar regions. ▪ In symptomatic participants with amyloidosis , insular cortex, medial frontal cortex, and prefrontal cortex demonstrated the most severe losses of glucose metabolism with increasing CDR. Lateral parietal and posterior superior temporal cortices retained glucose metabolism even for CDR > 0.5. ▪ NMF models of glucose metabolism are consistent with models arising from principal components, or eigenbrains, while adding additional regional interpretability. ▪ NMF patterns correlated with regions catalogued in Neurosynth. Following corrections for spatial autocorrelations, NMF patterns revealed meta-analytic identifications of patterns with Neurosynth topics of fear/reward, attention, memory, language, and movement with motor planning. Patterns varied with degrees of cognitive impairment.

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modeling

Metabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [18F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [18F]FDG kinetic parameters fully describing the tracer behavior (i.e., Ki, K1, k3); 3) assess MC interpretability in comparison to structural connectivity and FC. We developed a new approach based on Euclidean distance to calculate wi-MC from PET time-activity curves. The across-individual correlation of SUVR, Ki, K1, k3 produced different networks depending on the chosen [18F]FDG parameter (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). Our analyses demonstrate that calculating individual-level MC from dynamic PET is feasible and yields interpretable matrices that bear similarity to fMRI FC measures.

The Impact of Screening for Perioperative ICU Admission in Geriatric Hip Fracture Patients: A Retrospective Analysis

BACKGROUND

Hip fracture patients are a subset of trauma patients with high peri-operative mortality. To mitigate the mortality risk, the use of predictive scoring systems (e.g., RSI or Nomograms) for risk stratification and monitoring of high-risk patients in the intensive care unit (ICU) has been proposed. Screening patients for ICU admission with relatively low-cost tools may achieve high-quality, low-cost care. The aim of this study was to assess the effectiveness and feasibility of screening postoperative hip fracture patients for ICU admission.

METHODS

This is a retrospective single-site study comparing two groups of patients, before and after implementation of a hip fracture postoperative screening intervention in a level 1 trauma center in the United States. All hip fracture patients > 55 years of age admitted to the hospital between January 2021 and May 2023 were included. Trauma team members assessed and screened patients postoperatively in the post-anesthesia care unit (PACU), ordering standardized tests, including laboratory tests, a chest x-ray, and electrocardiogram (EKG). Assessment of the effect of the intervention included a comparison of a number of major adverse events (MAEs), mortality, planned and unplanned ICU admissions, ICU length of stay (LOS), and hospital LOS between pre- and post-intervention groups. Propensity score (PS) estimates were used to compare outcomes between the matched participants in the sample. A predictive model for ICU admission for the overall sample was estimated, and discriminative ability was assessed with an area under the curve (AUC) receiver operator characteristics (ROC) analysis. Lastly, feasibility was assessed by compliance with screening intervention and charges per patient related to the intervention.

RESULTS

The sample consisted of 290 patients in the pre-intervention and 180 patients in the post-intervention groups, respectively, with a mean age of 81.4 ± (9.9) years. There was a significant increase (p<0.01) in planned ICU admissions (OR=2.387, 95% CI (1.430, 3.983)) after screening protocol implementation. There was no significant difference between the pre-intervention group and post-intervention group in the number of MAEs (p=0.392), mortality (p=0.591), ICU LOS (p=0.617), and hospital LOS (p=0.151). When the PS-matched sample (n=424) was analyzed, there was a significant decrease (p=0.45) in unplanned ICU admissions (OR=6.40, 95% CI (0.81, 50.95)) after protocol implementation. Anticoagulants, emergency department (ED) respiratory rate (RR), injury severity score (ISS), number of comorbidities, substance use disorder (SAD), peripheral artery disease (PAD), and chronic obstructive pulmonary disease (COPD) were significant predictors of ICU admission (p=0.002, 0.022, 0.030, 0.034, 0.039, 0.039, and 0.042), respectively, and, demonstrated the discriminative ability between high and low risk for ICU admission (AUC=0.597, 0.587, 0.581, 0.578, 0.513, and 0.587, respectively). The screening intervention was achievable with 99% compliance (Kappa estimate 0.94) among trauma team members with an average charge of $282 per patient.

CONCLUSION

The addition of a postoperative screening intervention for hip fracture patients > 55 years of age is achievable and decreases unplanned ICU admissions in matched samples. Presenting clinical indicators and comorbidities are associated with ICU admission and provide sufficient discriminatory ability as criteria for ICU admission.

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning

OBJECTIVE

Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state networks (RSNs) with a reduced scanning time would lead to improved patient comfort while reducing the cost per scan. The aims of the present study were to develop a deep 3D convolutional neural network (3DCNN) capable of voxel-wise mapping of language (LAN) and motor (MOT) RSNs with minimal quantities of RS-fMRI data.

METHODS

Imaging data were gathered from multiple ongoing studies at Washington University School of Medicine and other thoroughly characterized, publicly available data sets. All study participants (n = 2252 healthy adults) were cognitively screened and completed structural neuroimaging and RS-fMRI. Random permutations of RS-fMRI regions of interest were used to train a 3DCNN. After training, model inferences were compared using varying amounts of RS-fMRI data from the control data set as well as 5 patients with glioblastoma multiforme.

RESULTS

The trained model achieved 96% out-of-sample validation accuracy on data encompassing a large age range collected on multiple scanner types and varying sequence parameters. Testing on out-of-sample control data showed 97.9% similarity between results generated using either 50 or 200 RS-fMRI time points, corresponding to approximately 2.5 and 10 minutes, respectively (96.9% LAN, 96.3% MOT true-positive rate). In evaluating data from patients with brain tumors, the 3DCNN was able to accurately map LAN and MOT networks despite structural and functional alterations.

CONCLUSIONS

Functional maps produced by the 3DCNN can inform surgical planning in patients with brain tumors in a time-efficient manner. The authors present a highly efficient method for presurgical functional mapping and thus improved functional preservation in patients with brain tumors.

Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survival

Glioblastoma, a highly aggressive form of brain tumor, is a brain-wide disease. We evaluated the impact of tumor burden on whole brain resting-state functional magnetic resonance imaging (rs-fMRI) activity. Specifically, we analyzed rs-fMRI signals in the temporal frequency domain in terms of the power-law exponent and fractional amplitude of low-frequency fluctuations (fALFF). We contrasted 189 patients with newly-diagnosed glioblastoma versus 189 age-matched healthy reference participants from an external dataset. The patient and reference datasets were matched for age and head motion. The principal finding was markedly flatter spectra and reduced grey matter fALFF in the patients as compared to the reference dataset. We posit that the whole-brain spectral change is attributable to global dysregulation of excitatory and inhibitory balance and metabolic demand in the tumor-bearing brain. Additionally, we observed that clinical comorbidities, in particular, seizures, and MGMT promoter methylation, were associated with flatter spectra. Notably, the degree of change in spectra was predictive of overall survival. Our findings suggest that frequency domain analysis of rs-fMRI activity provides prognostic information in glioblastoma patients and offers a means of noninvasively studying the effects of glioblastoma on the whole brain.

Abstract 700: Induction of cancer-specific T-cell responses in patients immunized with P10s-PADRE vaccine

Introduction: HR+/HER2− breast cancer is the most common form of breast cancer in the United States. HR+/HER2− tumors are known for a low number of tumor-infiltrating lymphocytes (TILs) and considered less immunogenic than other breast cancer subtypes. We have demonstrated that vaccination with P10s-PADRE, a carbohydrate-mimetic-based peptide, cancer vaccine in combination with standard-of-care chemotherapy in HR+/HER2− breast cancer patients led to an increase in TILs and stromal CD3+ T cells. The current study was performed to determine the vaccine specificity and anti-tumor functionality of T cells in treated patients.

Methods: Peripheral blood mononuclear cells (PBMCs) collected at the baseline and after vaccination were used in T-cell assays by multi-color ELISpot, examining Th1, Th2, and cytotoxic responses. PBMCs were also interrogated for the vaccine-induced changes in immune gene expression by next-generation RNA-seq analysis.

Results: We observed a significant increase in IFN-g, but not in IL-5 or IL-10, responses in post-immune PBMCs after stimulation with P10s, P10s-PADRE and polyclonal stimulation of T cells by anti-CD3/CD28 antibodies. Stimulation with cancer cell lysate resulted in a strikingly high IFN-g response in post-immune samples. Determining the trio of IFN-g, GzB, and IL-2 together with CD4/CD8 cell proliferation assays of consequent post vaccination specimens established the dynamics of effector T-cell populations. RNA-seq data clearly distinguished post-treatment samples by the increase in immune cell activation, cytokine response, and antigen presentation.

Conclusions: The data indicate that immunization of HR+/HER2− breast cancer patients with P10s-PADRE in combination with chemotherapy leads to specific activation of T-cells that recognize breast cancer cells. Improving immunogenicity of such immunologically cold tumors could increase the effectiveness of standard therapeutic approaches.

Citation Format: John J. Lee, Bernice C. Nounamo, Fariba Jousheghany, Issam Makhoul, Eric R. Siegel, Thomas Kieber-Emmons, Behjatolah Monzavi-Karbassi. Induction of cancer-specific T-cell responses in patients immunized with P10s-PADRE vaccine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 700.

Resting state network mapping in individuals using deep learning

Introduction

Resting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases to individual network mapping for pre-surgical planning of tumor resections. Reproducibility of these results has been shown to require a substantial amount of high-quality data, which is not often available in clinical or research settings.

Methods

In this work, we report voxelwise mapping of a standard set of RSNs using a novel deep 3D convolutional neural network (3DCNN). The 3DCNN was trained on publicly available functional MRI data acquired in n = 2010 healthy participants. After training, maps that represent the probability of a voxel belonging to a particular RSN were generated for each participant, and then used to calculate mean and standard deviation (STD) probability maps, which are made publicly available. Further, we compared our results to previously published resting state and task-based functional mappings.

Results

Our results indicate this method can be applied in individual subjects and is highly resistant to both noisy data and fewer RS-fMRI time points than are typically acquired. Further, our results show core regions within each network that exhibit high average probability and low STD.

Discussion

The 3DCNN algorithm can generate individual RSN localization maps, which are necessary for clinical applications. The similarity between 3DCNN mapping results and task-based fMRI responses supports the association of specific functional tasks with RSNs.

Preoperative functional connectivity by magnetic resonance imaging for refractory neocortical epilepsy

Objective

Patients with refractory epilepsy experience extensive and invasive clinical testing for seizure onset zones treatable by surgical resection. However, surgical resection can fail to provide therapeutic benefit, and patients with neocortical epilepsy have the poorest therapeutic outcomes. This case series studied patients with neocortical epilepsy who were referred for surgical treatment. Prior to surgery, patients volunteered for resting-state functional magnetic resonance imaging (rs-fMRI) in addition to imaging for the clinical standard of care. This work examined the variability of functional connectivity in patients, estimated from rs-fMRI, for associations with surgical outcomes.

Methods

This work examined pre-operative structural imaging, pre-operative rs-fMRI, and post-operative structural imaging from seven epilepsy patients. Review of the clinical record provided Engel classifications for surgical outcomes. A novel method assessed pre-operative rs-fMRI from patients using comparative rs-fMRI from a large cohort of healthy control subjects and estimated Gibbs distributions for functional connectivity in patients compared to healthy controls.

Results

Three patients had Engel classification Ia, one patient had Engel classification IIa, and three patients had Engel classification IV. Metrics for variability of functional connectivity, including absolute differences of the functional connectivity of each patient from healthy control averages and probabilistic scores for absolute differences, were higher for patients classified as Engel IV, for whom epilepsy surgery provided no meaningful improvement.

Significance

This work continues on-going efforts to use rs-fMRI to characterize abnormal functional connectivity in the brain. Preliminary evidence indicates that the topography of variant functional connectivity in epilepsy patients may be clinically relevant for identifying patients unlikely to have favorable outcomes after epilepsy surgery. Widespread topographic variations of functional connectivity also support the hypothesis that epilepsy is a disease of brain resting-state networks.

The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images

OBJECTIVES

The KNee OsteoArthritis Prediction (KNOAP2020) challenge was organized to objectively compare methods for the prediction of incident symptomatic radiographic knee osteoarthritis within 78 months on a test set with blinded ground truth.

DESIGN

The challenge participants were free to use any available data sources to train their models. A test set of 423 knees from the Prevention of Knee Osteoarthritis in Overweight Females (PROOF) study consisting of magnetic resonance imaging (MRI) and X-ray image data along with clinical risk factors at baseline was made available to all challenge participants. The ground truth outcomes, i.e., which knees developed incident symptomatic radiographic knee osteoarthritis (according to the combined ACR criteria) within 78 months, were not provided to the participants. To assess the performance of the submitted models, we used the area under the receiver operating characteristic curve (ROCAUC) and balanced accuracy (BACC).

RESULTS

Seven teams submitted 23 entries in total. A majority of the algorithms were trained on data from the Osteoarthritis Initiative. The model with the highest ROCAUC (0.64 (95% confidence interval (CI): 0.57-0.70)) used deep learning to extract information from X-ray images combined with clinical variables. The model with the highest BACC (0.59 (95% CI: 0.52-0.65)) ensembled three different models that used automatically extracted X-ray and MRI features along with clinical variables.

CONCLUSION

The KNOAP2020 challenge established a benchmark for predicting incident symptomatic radiographic knee osteoarthritis. Accurate prediction of incident symptomatic radiographic knee osteoarthritis is a complex and still unsolved problem requiring additional investigation.

Structural gray matter alterations in glioblastoma and high-grade glioma-A potential biomarker of survival

Background

Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients.

Methods

We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients' associated changes in CT as a potential biomarker of overall survival.

Results

Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients' cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%.

Conclusions

These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients.

Blood pressure and clinical outcomes in patients with diabetes and stable coronary artery disease in THEMIS

Background

Various BP characteristics, e.g., systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), as well as heart rate (HR) may affect the risk of both cardiovascular events and bleeding events. However, the exact way in which these characteristics and outcomes are associated among patients with diabetes and stable coronary artery disease (CAD) remains debated. Moreover, it is unknown whether the risks and benefits of intensified antiplatelet therapy in this patient population are affected by their baseline BP and HR.

Purpose

To assess the relationship between BP components (including HR) and cardiovascular and bleeding events, and to determine if the effects of ticagrelor vs. placebo varied across the BP and HR spectrum, in patients with diabetes and stable CAD.

Methods

THEMIS was a randomized, controlled trial in which 19,220 individuals ≥50 years of age with stable CAD and type 2 diabetes were randomized to receive either ticagrelor plus aspirin or placebo plus aspirin. Patients with a prior myocardial infarction or stroke, or already on dual antiplatelet therapy, were excluded. The primary efficacy outcome was a composite of cardiovascular death, myocardial infarction, or stroke. The primary safety outcome was TIMI major bleeding. We examined prognostic implications of BP components using 1) restricted cubic splines for the overall trends with outcomes; 2) Cox proportional-hazards regression models with predefined BP component intervals adjusted for demographic, clinical, and laboratory variables; and 3) Cox regression models for the effects of ticagrelor vs. placebo on outcomes across the spectrum of BP component values (test for interaction). THEMIS is registered at ClinicalTrials.gov (NCT01991795).

Results

Mean values of baseline BP components were similar between the two study groups. Median follow-up duration was 39.9 months (range 0–57), with 1554 primary efficacy events and 306 primary safety events occurring over the course of the study. All BP components (including HR) displayed various, independent relationships with the tested outcomes. For example, in adjusted spline models, SBP displayed non-linear relationships with the primary outcome, all-cause death, any bleeding, serious adverse events, and intracranial bleeding, and linear relationships with the remaining outcomes. Figure 1 shows the associations of each BP component with the primary efficacy outcome. BP components did not substantially modify the risks and benefits of ticagrelor vs. placebo for the tested outcomes.

Conclusions

BP components were independently associated with efficacy and safety outcomes in patients with stable CAD and type 2 diabetes. However, no important modification of BP components on the effect of ticagrelor vs. placebo was detected.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): AstraZeneca

Modeling venous plasma samples in [18F] FDG PET studies: a nonlinear mixed-effects approach

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.

Plasma-Based Measurements of Tumor Heterogeneity Correlate with Clinical Outcomes in Metastatic Colorectal Cancer

Sequencing circulating tumor DNA (ctDNA) from liquid biopsies may better assess tumor heterogeneity than limited sampling of tumor tissue. Here, we explore ctDNA-based heterogeneity and its correlation with treatment outcome in STEAM, which assessed efficacy and safety of concurrent and sequential FOLFOXIRI-bevacizumab (BEV) vs. FOLFOX-BEV for first-line treatment of metastatic colorectal cancer. We sequenced 146 pre-induction and 89 post-induction patient plasmas with a 198-kilobase capture-based assay, and applied Mutant-Allele Tumor Heterogeneity (MATH), a traditionally tissue-based calculation of allele frequency distribution, on somatic mutations detected in plasma. Higher levels of MATH, particularly in the post-induction sample, were associated with shorter progression-free survival (PFS). Patients with high MATH vs. low MATH in post-induction plasma had shorter PFS (7.2 vs. 11.7 months; hazard ratio, 3.23; 95% confidence interval, 1.85−5.63; log-rank p < 0.0001). These results suggest ctDNA-based tumor heterogeneity may have potential prognostic value in metastatic cancers.

Deep learning resting state fMRI lateralization of temporal lobe epilepsy

OBJECTIVE

Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for non-invasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional MRI (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients.

METHODS

2132 healthy controls and 32 pre-operative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data was used to generate training samples for a 3D convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure-onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions.

RESULTS

The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, while the resting state networks which colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with post-surgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel class > 1 compared to Engel class 1.

SIGNIFICANCE

Non-invasive techniques capable of localizing the seizure-onset zone could improve pre-surgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.

Genetic and phenotypic characteristics of Clostridium (Clostridioides) difficile from canine, bovine, and pediatric populations

Objectives:

Carriage of Clostridioides difficile by different species of animals has led to speculation that animals could represent a reservoir of this pathogen for human infections. The objective of this study was to compare C. difficile isolates from humans, dogs, and cattle from a restricted geographic area.

Methods:

C. difficile isolates from 36 dogs and 15 dairy calves underwent whole genome sequencing, and phenotypic assays assessing growth and virulence were performed. Genomes of animal-derived isolates were compared to 29 genomes of isolates from a pediatric population as well as 44 reference genomes.

Results:

Growth rates and relative cytotoxicity of isolates were significantly higher and lower, respectively, in bovine-derived isolates compared to pediatric- and canine-derived isolates. Analysis of core genes showed clustering by host species, though in a few cases, human strains co-clustered with canine or bovine strains, suggesting possible interspecies transmission. Geographic differences (e.g., farm, litter) were small compared to differences between species. In an analysis of accessory genes, the total number of genes in each genome varied between host species, with 6.7% of functional orthologs differentially present/absent between host species and bovine-derived strains having the lowest number of genes. Canine-derived isolates were most likely to be non-toxigenic and more likely to carry phages. A targeted study of episomes identified in local pediatric strains showed sharing of a methicillin-resistance plasmid with dogs, and historic sharing of a wide range of episomes across hosts. Bovine-derived isolates harbored the widest variety of antibiotic-resistance genes, followed by canine

Conclusions:

While C. difficile isolates mostly clustered by host species, occasional co-clustering of canine and pediatric-derived isolates suggests the possibility of interspecies transmission. The presence of a pool of resistance genes in animal-derived isolates with the potential to appear in humans given sufficient pressure from antibiotic use warrants concern.

Abstract P2-14-15: Timing of the immunization defines immune signature of a peptide cancer vaccine combined with Neoadjuvant chemotherapy in HR+ breast cancer patients

Background: We have developed P10s-PADRE, a carbohydrate-mimetic-based peptide, cancer vaccine and demonstrated its safety and immunogenicity in a Phase I clinical trial performed in stage IV breast cancer patients. HR+/HER2- breast cancer is the most common form of breast cancer diagnosed in the United States. These patients face a persistent risk of distant recurrence long after completion of their treatment and new strategies to activate anti-tumor immune responses can improve outcomes of standard therapies. The current study was performed to examine the feasibility, safety and immunogenicity of adding P10s-PADRE to standard-of-care chemotherapy in HR+/HER2− early-stage breast cancer patients. Methods: Five combination schedules were designed based on the timing of immunizations relative to a standard-of-care neoadjuvant chemotherapy regimen. Induction of on-treatment antibody and cellular responses, including T-cells, natural killer (NK) cells, and cytokines was determined. Tumor-infiltrating lymphocytes were quantified in core and surgical biopsies. The data were used to define the treatment effect in general and the vaccine contribution in particular. Results: Combination of P10s-PADRE with chemotherapy was safe and immunogenic. Antibody response was superior in a particular combination schedule, called schedule C, where 3 weekly immunizations preceded the first dose of chemotherapy. We observed that the schedule C, relative to other schedules, displayed an increase in CD16 expression on NK cells, a drop in serum IFN-γ, and an increase in quantity of stromal TILs in residual tumors. Subjects demonstrated a significant reduction in the size of their primary tumor and three subjects achieved pCR. Conclusions: The timing of the immunization relative to the chemotherapy seems to define the type and strength of the immune responses elicited. A particular combination schedule, schedule C, appears promising and the results warrant the conduct of randomized phase II trials.

Citation Format: Issam Makhoul, Saddam M Ibrahim, Muhammad Abu-Rmaileh, Fariba Jousheghany, Eric Siegel, Lora J Rogers, John J Lee, Sergio Pina-Oviedo, Ginell R Post, Thaddeus Beck, Thomas Kieber-Emmons, Behjatolah Monzavi-Karbassi. Timing of the immunization defines immune signature of a peptide cancer vaccine combined with Neoadjuvant chemotherapy in HR+ breast cancer patients [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-14-15.

Distinct tumor-infiltrating lymphocyte landscapes are associated with clinical outcomes in localized non-small-cell lung cancer

BACKGROUND

Despite the importance of tumor-infiltrating T lymphocytes (TILs) in cancer biology, the relationship between TIL phenotypes and their prognostic relevance for localized non-small-cell lung cancer (NSCLC) has not been well established.

PATIENTS AND METHODS

Fresh tumor and normal adjacent tissue was prospectively collected from 150 patients with localized NSCLC. Tissue was comprehensively characterized by high-dimensional flow cytometry of TILs integrated with immunogenomic data from multiplex immunofluorescence, T-cell receptor sequencing, exome sequencing, RNA sequencing, targeted proteomics, and clinicopathologic features.

RESULTS

While neither the magnitude of TIL infiltration nor specific TIL subsets were significantly prognostic alone, the integration of high-dimensional flow cytometry data identified two major immunotypes (IM1 and IM2) that were predictive of recurrence-free survival independent of clinical characteristics. IM2 was associated with poor prognosis and characterized by the presence of proliferating TILs expressing cluster of differentiation 103, programmed cell death protein 1, T-cell immunoglobulin and mucin-domain containing protein 3, and inducible T-cell costimulator. Conversely, IM1 was associated with good prognosis and differentiated by an abundance of CD8⁺ T cells expressing cytolytic enzymes, CD4⁺ T cells lacking the expression of inhibitory receptors, and increased levels of B-cell infiltrates and tertiary lymphoid structures. While increased B-cell infiltration was associated with good prognosis, the best prognosis was observed in patients with tumors exhibiting high levels of both B cells and T cells. These findings were validated in patient tumors from The Cancer Genome Atlas.

CONCLUSIONS

Our study suggests that although the number of infiltrating T cells is not associated with patient survival, the nature of the infiltrating T cells, resolved in distinct TIL immunotypes, is prognostically relevant in NSCLC and may inform therapeutic approaches to clinical care.

Efflux pump gene expression study using RNA-seq in multidrug-resistant TB

BACKGROUND: The mechanism underlying kanamycin (KM) resistance in Mycobacterium tuberculosis is not well understood, although efflux pump proteins are thought to play a role. This study used RNA-seq data to investigate changes in the expression levels of efflux pump genes following exposure to KM.METHODS: RNA expression of efflux pump and regulatory genes following exposure to different concentrations of KM (minimum inhibitory concentration MIC 25 and MIC50) in rrs wild-type strain and rrs A1401G mutated strain were compared with the control group.RESULTS: The selected strains had differential RNA expression patterns. Among the 71 putative efflux pump and regulatory genes, 46 had significant fold changes, and 12 genes (Rv0842, Rv1146, Rv1258c, Rv1473, Rv1686c, Rv1687c, Rv1877, Rv2038c, Rv3065, Rv3197a, Rv3728 and Rv3789) that were overexpressed following exposure to KM were thought to contribute to drug resistance. Rv3197A (whiB7) showed a distinct fold change based on the concentration of KM.CONCLUSION: The significant changes in the expression of the efflux pump and regulatory genes following exposure to KM may provide insights into the identification of a new resistance mechanism.

Modeling the Effects of HIV and Aging on Resting-State Networks Using Machine Learning

BACKGROUND

The relationship between HIV infection, the functional organization of the brain, cognitive impairment, and aging remains poorly understood. Understanding disease progression over the life span is vital for the care of people living with HIV (PLWH).

SETTING

Virologically suppressed PLWH (n = 297) on combination antiretroviral therapy and 1509 HIV-uninfected healthy controls were evaluated. PLWH were further classified as cognitively normal (CN) or cognitively impaired (CI) based on neuropsychological testing.

METHODS

Feature selection identified resting-state networks (RSNs) that predicted HIV status and cognitive status within specific age bins (younger than 35 years, 35-55 years, and older than 55 years). Deep learning models generated voxelwise maps of RSNs to identify regional differences.

RESULTS

Salience (SAL) and parietal memory networks (PMNs) differentiated individuals by HIV status. When comparing controls with PLWH CN, the PMN and SAL had the strongest predictive strength across all ages. When comparing controls with PLWH CI, the SAL, PMN, and frontal parietal network (FPN) were the best predictors. When comparing PLWH CN with PLWH CI, the SAL, FPN, basal ganglia, and ventral attention were the strongest predictors. Only minor variability in predictive strength was observed with aging. Anatomically, differences in RSN topology occurred primarily in the dorsal and rostral lateral prefrontal cortex, cingulate, and caudate.

CONCLUSION

Machine learning identified RSNs that classified individuals by HIV status and cognitive status. The PMN and SAL were sensitive for discriminating HIV status, with involvement of FPN occurring with cognitive impairment. Minor differences in RSN predictive strength were observed by age. These results suggest that specific RSNs are affected by HIV, aging, and HIV-associated cognitive impairment.

A multi-scale map of cell structure fusing protein images and interactions

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

Phase 3, randomized, open-label study of pembrolizumab plus lenvatinib versus chemotherapy for first-line treatment of advanced or recurrent endometrial cancer: ENGOT-en9/LEAP-001

Background

Pembrolizumab plus lenvatinib is a novel combination with promising efficacy in patients with advanced and recurrent endometrial cancer. This combination demonstrated high objective response rates in a single-arm phase 1b/2 trial of lenvatinib plus pembrolizumab in patients with advanced endometrial cancer (KEYNOTE-146/Study 111) after ≤2 previous lines of therapy. In a randomized phase 3 trial of lenvatinib in combination with pembrolizumab versus treatment of physician's choice in patients with advanced endometrial cancer (KEYNOTE-775/Study 309), after 1‒2 previous lines of therapy (including neoadjuvant/adjuvant), this combination improved objective response rates, progression-free survival, and overall survival compared with chemotherapy.

Primary Objective

To compare the efficacy and safety of first-line pembrolizumab plus lenvatinib versus paclitaxel plus carboplatin in patients with newly diagnosed stage III/IV or recurrent endometrial cancer, with measurable or radiographically apparent disease.

Study Hypothesis

Pembrolizumab plus lenvatinib is superior to chemotherapy with respect to progression-free survival and overall survival in patients with mismatch repair-proficient tumors and all patients (all-comers).

Trial Design

Phase 3, randomized (1:1), open-label, active-controlled trial. Patients will receive pembrolizumab intravenously every 3 weeks plus lenvatinib orally daily or paclitaxel plus carboplatin intravenously every 3 weeks, stratified by mismatch repair status (proficient vs deficient). Patients with mismatch repair-proficient tumors will be further stratified by Eastern Cooperative Oncology Group performance status (0/1), measurable disease (yes/no), and prior chemotherapy and/or chemoradiation (yes/no).

Major Inclusion/Exclusion Criteria

Adults with stage III/IV/recurrent histologically confirmed endometrial cancer that is measurable or radiographically apparent per blinded independent central review. Patients may have received previous chemotherapy only as neoadjuvant/adjuvant therapy and/or concurrently with radiation. Patients with carcinosarcoma (malignant mixed Müllerian tumor), endometrial leiomyosarcoma, or other high grade sarcomas, or endometrial stromal sarcomas were excluded.

Primary Endpoints

Progression-free and overall survival (dual primary endpoints).

Sample Size

About 875 patients.

Estimated Dates for Completing Accrual and Presenting Results

Enrollment is expected to take approximately 24 months, with presentation of results in 2022.

Trial Registration

ClinicalTrials.gov, NCT03884101.

Interpretation of cancer mutations using a multiscale map of protein systems

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.

Screen-Based Simulation for Training and Automated Assessment of Teamwork Skills: Comparing 2 Modes With Different Interactivity

INTRODUCTION

The need for teamwork training is well documented; however, teaching these skills is challenging given the logistics of assembling individual team members together to train in person. We designed 2 modes of screen-based simulation for training teamwork skills to assess whether interactivity with nonplayer characters was necessary for in-game performance gains or for player satisfaction with the experience.

METHODS

Mixed, randomized, repeated measures study with licensed healthcare providers block-stratified and randomized to evaluation-participant observes and evaluates the team player in 3 scenarios-and game play-participant is immersed as the leader in the same 3 scenarios. Teamwork construct scores (leadership, communication, situation monitoring, mutual support) from an ontology-based, Bayesian network assessment model were analyzed using mixed randomized repeated measures analyses of variance to compare performance, across scenarios and modes. Learning was measured by pretest and posttest quiz scores. User experience was evaluated using χ2 analyses.

RESULTS

Among 166 recruited and randomized participants, 120 enrolled in the study and 109 had complete data for analysis. Mean composite teamwork Bayesian network scores improved for successive scenarios in both modes, with evaluation scores statistically higher than game play for every teamwork construct and scenario (r = 0.73, P = 0.000). Quiz scores improved from pretest to posttest (P = 0.004), but differences between modes were not significant.

CONCLUSIONS

For training teamwork skills using screen-based simulation, interactivity of the player with the nonplayer characters is not necessary for in-game performance gains or for player satisfaction with the experience.

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform

Background

Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinically significant information. The objective of this research is to assess the performance of a deep learning algorithm to detect murmurs and clinically significant valvular heart disease using recordings from a commercial digital stethoscope platform.

Methods and Results

Using >34 hours of previously acquired and annotated heart sound recordings, we trained a deep neural network to detect murmurs. To test the algorithm, we enrolled 962 patients in a clinical study and collected recordings at the 4 primary auscultation locations. Ground truth was established using patient echocardiograms and annotations by 3 expert cardiologists. Algorithm performance for detecting murmurs has sensitivity and specificity of 76.3% and 91.4%, respectively. By omitting softer murmurs, those with grade 1 intensity, sensitivity increased to 90.0%. Application of the algorithm at the appropriate anatomic auscultation location detected moderate‐to‐severe or greater aortic stenosis, with sensitivity of 93.2% and specificity of 86.0%, and moderate‐to‐severe or greater mitral regurgitation, with sensitivity of 66.2% and specificity of 94.6%.

Conclusions

The deep learning algorithm’s ability to detect murmurs and clinically significant aortic stenosis and mitral regurgitation is comparable to expert cardiologists based on the annotated subset of our database. The findings suggest that such algorithms would have utility as front‐line clinical support tools to aid clinicians in screening for cardiac murmurs caused by valvular heart disease.

Registration

URL: https://clinicaltrials.gov; Unique Identifier: NCT03458806.

Machine Learning Analytics of Resting-State Functional Connectivity Predicts Survival Outcomes of Glioblastoma Multiforme Patients

Glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy. Due to its poor prognosis with currently available treatments, there is a pressing need for easily accessible, non-invasive techniques to help inform pre-treatment planning, patient counseling, and improve outcomes. In this study we determined the feasibility of resting-state functional connectivity (rsFC) to classify GBM patients into short-term and long-term survival groups with respect to reported median survival (14.6 months). We used a support vector machine with rsFC between regions of interest as predictive features. We employed a novel hybrid feature selection method whereby features were first filtered using correlations between rsFC and OS, and then using the established method of recursive feature elimination (RFE) to select the optimal feature subset. Leave-one-subject-out cross-validation evaluated the performance of models. Classification between short- and long-term survival accuracy was 71.9%. Sensitivity and specificity were 77.1 and 65.5%, respectively. The area under the receiver operating characteristic curve was 0.752 (95% CI, 0.62–0.88). These findings suggest that highly specific features of rsFC may predict GBM survival. Taken together, the findings of this study support that resting-state fMRI and machine learning analytics could enable a radiomic biomarker for GBM, augmenting care and planning for individual patients.

Multi-reference global registration of individual A-lines in adaptive optics optical coherence tomography retinal images

SIGNIFICANCE

Adaptive optics optical coherence tomography (AO-OCT) technology enables non-invasive, high-resolution three-dimensional (3D) imaging of the retina and promises earlier detection of ocular disease. However, AO-OCT data are corrupted by eye-movement artifacts that must be removed in post-processing, a process rendered time-consuming by the immense quantity of data.

AIM

To efficiently remove eye-movement artifacts at the level of individual A-lines, including those present in any individual reference volume.

APPROACH

We developed a registration method that cascades (1) a 3D B-scan registration algorithm with (2) a global A-line registration algorithm for correcting torsional eye movements and image scaling and generating global motion-free coordinates. The first algorithm corrects 3D translational eye movements to a single reference volume, accelerated using parallel computing. The second algorithm combines outputs of multiple runs of the first algorithm using different reference volumes followed by an affine transformation, permitting registration of all images to a global coordinate system at the level of individual A-lines.

RESULTS

The 3D B-scan algorithm estimates and corrects 3D translational motions with high registration accuracy and robustness, even for volumes containing microsaccades. Averaging registered volumes improves our image quality metrics up to 22 dB. Implementation in CUDA™ on a graphics processing unit registers a 512  ×  512  ×  512 volume in only 10.6 s, 150 times faster than MATLAB™ on a central processing unit. The global A-line algorithm minimizes image distortion, improves regularity of the cone photoreceptor mosaic, and supports enhanced visualization of low-contrast retinal cellular features. Averaging registered volumes improves our image quality up to 9.4 dB. It also permits extending the imaging field of view (∼2.1  ×  ) and depth of focus (∼5.6  ×  ) beyond what is attainable with single-reference registration.

CONCLUSIONS

We can efficiently correct eye motion in all 3D at the level of individual A-lines using a global coordinate system.

Homotopic functional connectivity disruptions in glioma patients are associated with tumor malignancy and overall survival

Background

Gliomas exhibit widespread bilateral functional connectivity (FC) alterations that may be associated with tumor grade. Limited studies have examined the connection-level mechanisms responsible for these effects. Given the typically strong FC observed between mirroring/homotopic brain regions in healthy subjects, we hypothesized that homotopic connectivity (HC) is altered in low-grade and high-grade glioma patients and the extent of disruption is associated with tumor grade and predictive of overall survival (OS) in a cohort of de novo high-grade glioma (World Health Organization [WHO] grade 4) patients.

Methods

We used a mirrored FC-derived cortical parcellation to extract blood-oxygen-level-dependent (BOLD) signals and to quantify FC differences between homotopic pairs in normal-appearing brain in a retrospective cohort of glioma patients and healthy controls.

Results

Fifty-nine glioma patients (WHO grade 2, n = 9; grade 4 = 50; mean age, 57.5 years) and 30 healthy subjects (mean age, 65.9 years) were analyzed. High-grade glioma patients showed lower HC compared with low-grade glioma patients and healthy controls across several cortical locations and resting-state networks. Connectivity disruptions were also strongly correlated with hemodynamic lags between homotopic regions. Finally, in high-grade glioma patients with known survival times (n = 42), HC in somatomotor and dorsal attention networks were significantly correlated with OS.

Conclusions

These findings demonstrate an association between tumor grade and HC alterations that may underlie global FC changes and provide prognostic information.

Knowledge, attitudes and binge drinking among urban Chinese university students in Hong Kong

Background

Although dormitory residents have been identified as a high-risk group for alcohol misuse in Chinese university settings, the factors associated with their drinking behaviors has not be characterized.

Methods

A cross-sectional study was conducted among hostel residents in two Hong Kong universities (n = 1455) using self-administered, anonymous surveys. In addition to examining the knowledge levels and drinking-related attitudes, we examined the factors associated with binge drinking in this population using multivariable regression analysis.

Results

Among university dormitory residents, the prevalence of past-month binge drinking was 26.8% among males and 12.8% among females. It was noted that although respondents demonstrated attitudes conducive towards alcohol-free socialization, they exhibited low levels of alcohol-related knowledge (mean knowledge score: 3.3/ 10, SD = 2.0). While about 59% were aware that alcohol is a carcinogen and that some medications should not be taken with alcohol, only 10.4% were familiar with symptoms of alcohol poisoning and only 23% were familiar with relative amounts of alcohol in different beverage categories. Of the respondents the factors independently associated with past-month binge drinking were: male sex, older age, full-time hostel residence, drinking roommates, drinking romantic partner, participation in drinking games, and having pro-alcohol attitudes (OR ranging from 1.33-3.69). Alcohol-related knowledge was not associated with binge drinking.

Conclusions

Although southern China is a low alcohol consumption area, binge drinking is common among university residents and requires multi-prong interventions. Heavy drinking is a neglected health problem among urban Chinese university students. Interventions targeting binge drinkers need to counteract pro-alcohol attitudes and peer effects. Increasing alcohol knowledge may additionally help to reduce alcohol-related harms in this age group.

Key messages

Urban Chinese university dormitory residents demonstrate low levels of alcohol knowledge. Pro-alcohol attitudes and peers effects need to be addressed in university anti-binge drinking interventions.

Second-hand harms of alcohol use in urban Chinese university students: A study from Hong Kong

Background

Although second-harms alcohol harms, harms caused by the drinking of others, may contribute significantly to the public health burden of alcohol, these harms are an understudied area of public health research. This study aims to examine second-hand alcohol harms in among urban Chinese university students residing on campus who are were previously identified as a high risk group for alcohol misuse.

Methods

A cross-sectional study was conducted among hostel residents in two Hong Kong universities (n = 1455) using self-administered, anonymous surveys. We examined the prevalance and the factors associated with second-hand alcohol harms this population using multivariable regression analysis.

Results

Approximately 2/3 of the university residents experienced at least one second-hand drinking harm in the past year while 1/5 experienced 4 or more harms. The harms reported were: 1) inconveniences/disturbances (46.2%), psychological distress/anxiety/depression (32.9%), home arguments (28.3%), conflicts/arguments/insults in public (25.3%), worsened productivity/academics (22.2%), property damage/monetary loss (13.2%), accidents/injury/assault (11.7%) and having to deal with authorities/law enforcement (11.5%). Only 9.1% reported these harms to authorities. Participation in drinking games (OR = 1.44), having drinking roomates (OR = 1.37) or drinking romantic partner (OR = 1.89) were independently associated with likelihood of second-hand alcohol harms (p &lt; 0.05).

Conclusions

Although southern China is a low alcohol consumption region, there is a high prevalence of second-hand alcohol harms among university dorm residents. Universities in the region should rectify the near absence of alcohol-related topics in university health promotion.

Key messages

Harms from the drinking of others is a commonplace but underappreciated phenomenon among university campus residents. University health promotion in the region should include alcohol harms reduction topics.

Mapping of the Language Network With Deep Learning

Background: Pre-surgical functional localization of eloquent cortex with task-based functional MRI (T-fMRI) is part of the current standard of care prior to resection of brain tumors. Resting state fMRI (RS-fMRI) is an alternative method currently under investigation. Here, we compare group level language localization using T-fMRI vs. RS-fMRI analyzed with 3D deep convolutional neural networks (3DCNN).

Methods: We analyzed data obtained in 35 patients with brain tumors that had both language T-fMRI and RS-MRI scans during pre-surgical evaluation. The T-fMRI data were analyzed using conventional techniques. The language associated resting state network was mapped using a 3DCNN previously trained with data acquired in >2,700 normal subjects. Group level results obtained by both methods were evaluated using receiver operator characteristic analysis of probability maps of language associated regions, taking as ground truth meta-analytic maps of language T-fMRI responses generated on the Neurosynth platform.

Results: Both fMRI methods localized major components of the language system (areas of Broca and Wernicke). Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system.

Conclusion: 3DCNN was able to accurately localize the language network. Additionally, 3DCNN performance was remarkably tolerant of a limited quantity of RS-fMRI data.

Mapping language function with task-based vs. resting-state functional MRI

Background

Use of functional MRI (fMRI) in pre-surgical planning is a non-invasive method for pre-operative functional mapping for patients with brain tumors, especially tumors located near eloquent cortex. Currently, this practice predominantly involves task-based fMRI (T-fMRI). Resting state fMRI (RS-fMRI) offers an alternative with several methodological advantages. Here, we compare group-level analyses of RS-fMRI vs. T-fMRI as methods for language localization.

Purpose

To contrast RS-fMRI vs. T-fMRI as techniques for localization of language function.

Methods

We analyzed data obtained in 35 patients who had both T-fMRI and RS-fMRI scans during the course of pre-surgical evaluation. The RS-fMRI data were analyzed using a previously trained resting-state network classifier. The T-fMRI data were analyzed using conventional techniques. Group-level results obtained by both methods were evaluated in terms of two outcome measures: (1) inter-subject variability of response magnitude and (2) sensitivity/specificity analysis of response topography, taking as ground truth previously reported maps of the language system based on intraoperative cortical mapping as well as meta-analytic maps of language task fMRI responses.

Results

Both fMRI methods localized major components of the language system (areas of Broca and Wernicke) although not with equal inter-subject consistency. Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system.

Conclusion

We demonstrate several advantages of classifier-based mapping of language representation in the brain. Language T-fMRI activated task-general (i.e., not language-specific) functional systems in addition to areas of Broca and Wernicke. In contrast, classifier-based analysis of RS-fMRI data generated maps confined to language-specific regions of the brain.

Long-term clinical outcomes and prognostic indicators for focal impulse and rotor modulation guided ablation: A single-center observational study

BACKGROUND

Electrophysiologists have developed a computational mapping approach to localize sources that may perpetuate persistent atrial fibrillation (AF). Focal impulse and rotor modulation (FIRM)-guided ablation of these sources have produced variable results. The current study further assesses single-procedure success rates of FIRM-guided ablation for preventing AF or atrial tachyarrhythmia recurrence and analyzes different baseline characteristics as prognostic indicators for individuals experiencing these undesired outcomes.

METHODS

Seventy-one consecutive patients (mean age 64.58 ± 9.05 years and 36.6% female) with drug-refractory persistent AF with and without prior history of pulmonary vein antral isolation (PVAI) underwent FIRM-guided ablation. Patients without prior history of PVAI underwent FIRM-guided ablation in addition to de novo PVAI. Patients with prior history of PVAI had the pulmonary veins reassessed at the time of FIRM-guided ablation for reconnection as well as re-isolation, when necessary. These patients were then prospectively followed for AF and atrial tachyarrhythmia recurrence.

RESULTS

FIRM analysis revealed rotors in the right atrium in 66.2% (1.77 ± 1.53 mean rotors per patient) and in the left atrium in 85.9% (2.65 ± 1.52 mean rotors per patient) of patients analyzed in the current study. After a single FIRM-guided ablation procedure, AF and atrial tachyarrhythmia recurrence was demonstrated in 21.1% (15/71) and 33.8% (24/71) of patients, respectively. The entire cohort of patients were followed for a mean duration of 23.20 ± 8.38 months with the mean time to AF recurrence found to be 12.35 ± 10.44 months. Furthermore, valvular heart disease (i.e. moderate mitral or tricuspid regurgitation) was found to be a statistically significant independent predictor for AF recurrence following FIRM-guided ablation (p = .033).

CONCLUSIONS

FIRM-guided ablation in combination with PVAI is a suitable and effective approach for symptomatic individuals with drug-refractory persistent AF with and without prior history of PVAI. Randomized controlled studies are warranted.

A Comparison of Risk of Dislocation and Cause-Specific Revision Between Direct Anterior and Posterior Approach Following Elective Cementless Total Hip Arthroplasty

BACKGROUND

Use of the direct anterior approach (DAA) for total hip arthroplasty (THA) has increased over the last decade. We sought to investigate whether (1) a difference exists in dislocation risk for DAA compared with posterior THA, (2) a difference exists in risk for specific revision reasons, and (3) the likelihood of adverse 90-day postoperative events differs.

METHODS

We conducted a cohort study using data from Kaiser Permanente's Total Joint Replacement Registry. Patients aged ≥18 years who underwent primary cementless THA for osteoarthritis with a highly cross-linked polyethylene liner were included (2009-2017). Multivariable Cox proportional hazards regression was used to evaluate dislocation and cause-specific revision risks, and multivariable logistic regression was used to evaluate 90-day emergency department visits, 90-day unplanned readmissions, and 90-day complications (including deep infection, deep vein thrombosis, and pulmonary embolism).

RESULTS

Of 38,399 primary THA, 6428 (16.7%) were DAA. All-cause revision at 2-years follow-up was 1.78% (95% confidence interval [CI] = 1.46-2.17) for DAA and 2.28% (95% CI = 2.11-2.45) for posterior. After adjusting for covariates, DAA had a lower risk of dislocation (hazard ratio [HR] = 0.39, 95% CI = 0.29-0.53), revision for instability (HR = 0.33, 95% CI = 0.18-0.58), revision for periprosthetic fracture (HR = 0.57, 95% CI = 0.34-0.96), and readmission (odds ratio = 0.82, 95% CI = 0.67-0.99) compared with posterior approach but a higher risk of revision for aseptic loosening (HR = 2.26, 95% CI = 1.35-3.79).

CONCLUSION

While the DAA associated with lower risks of dislocation and revision for instability and periprosthetic fracture, it is associated with a higher revision risk for aseptic loosening. Surgeons should discuss these risks with their patients.

ENGOT-en9/LEAP-001: A phase III study of first-line pembrolizumab plus lenvatinib versus chemotherapy in advanced or recurrent endometrial cancer

TPS6106

Background: The prognosis for endometrial cancer (EC) can be favorable when diagnosed in early stages, but prognosis and overall survival are poor in patients with advanced or recurrent EC. First-line standard of care for patients with advanced or recurrent EC is paclitaxel and carboplatin chemotherapy; however, there is a need for more effective and tolerable therapies. In the phase Ib/II trial KEYNOTE-146, which assessed the PD-1 inhibitor pembrolizumab (pembro) in combination with the multikinase inhibitor lenvatinib, an objective response rate (ORR) of 38% was observed (N=108) in patients with previously treated advanced EC. ENGOT-en9/LEAP-001 (NCT03884101) is a randomized, open-label, active-controlled, phase III study investigating pembro + lenvatinib vs chemotherapy in patients with newly diagnosed advanced or recurrent EC. Methods: Patients with newly diagnosed advanced (stage III-IV) or recurrent EC not previously treated with antiangiogenic agents; systemic chemotherapy (unless within a chemoradiation regimen); PD-1, PD-L1, or PD-L2 inhibitors; or other T-cell receptor–targeted therapies will be eligible. Patients will be randomized 1:1 to receive pembro 200 mg every 3 wk (Q3W) + lenvatinib 20 mg daily or paclitaxel 175 mg/m2 Q3W + carboplatin AUC 6 Q3W. Randomization will be stratified on the basis of proficient vs deficient mismatch repair (pMMR vs dMMR) status. The pMMR population will be further stratified by prior chemoradiation (yes vs no), measurable disease (yes vs no), and ECOG performance status (0 vs. 1). Patients will continue on treatment for up to 35 cycles of pembro vs 7 cycles of chemotherapy or until initiation of a new anticancer treatment, unacceptable adverse events, or withdrawal of consent. Primary study endpoints are progression-free survival (per RECIST v1.1 by blinded independent central review) and overall survival. Secondary study endpoints are ORR, health-related quality of life, safety and tolerability, and lenvatinib pharmacokinetics. Exploratory endpoints will include disease control rate, clinical benefit rate, and duration of response. Enrollment is ongoing. Clinical trial information: NCT03884101.

Relationship between compliance and pulmonary vascular resistance in pulmonary arterial hypertension

Background

Pulmonary arterial compliance (PAC) was previously shown to be an important prognostic factor in pulmonary arterial hypertension (PAH), in addition to the conventional pulmonary vascular resistance (PVR). The product of PAC and PVR, the arterial time (RC) constant, expresses the logarithmic relationship between the hemodynamic parameters. The objective of the study was to test RC constant stability in PAH patients followed beyond 12 months after diagnosis, and to report possible RC variations in different etiologies.

Methods

Fourteen PAH patients followed between 2008 and 2019 were included. Type 1 PAH was defined as a mean pulmonary artery pressure (PAP) ≥25 mmHg at rest and PVR ≥3 Wood units (WU). All patients who fulfilled WHO group I PAH criteria and had undergone two right heart catheterizations at least 1 year apart were included. The recorded hemodynamic data for each patient were used to compute PVR and PAC.

Results

PAH etiologies included scleroderma (n=2), liver cirrhosis (n=1), hereditary hemorrhagic telangiectasia (HHT) (n=1), mixed connective tissue disease (MCTD) (n=3), and idiopathic (n=7). The RC constant remained stable for all 14 patients over a follow-up period of 3.9±2 years. Patients with MCTD displayed more favorable hemodynamics, evidenced by higher RC (12.54 vs. 10.01, P<0.01) and PAC values (2.59 vs. 1.62, P=0.02), when compared with non-MCTD PAH patients. For the entire cohort the mean PAP measured 51±14 mmHg at baseline, and 46±13 mmHg at follow-up, respectively.

Conclusions

The relationship between PAC and PVR remains stable in follow-up periods averaging 4 years, making compliance an important disease marker past the early stages. Patients with MCTD displayed more advantageous hemodynamic profiles when compared with patients with other PAH etiologies.

Comparison of Cardiovascular Outcomes by Dialysis Modality: A Systematic Review and Meta-Analysis

Debates exist regarding the merit of starting one dialysis modality over the other for improved cardiovascular outcomes. Five previously published prospective and retrospective cohort studies have reported inconsistent conclusions on this topic. The aim of this systematic review and meta-analysis is to evaluate the influence initiation of hemodialysis (HD) vs peritoneal dialysis (PD) may have on the relative risk (RR) of subsequent development of adverse cardiovascular events (ACVE) in patients with end-stage renal disease (ESRD). Of the 518 records identified, 5 cohort studies, assessing a total of 47,062 patients were included in the meta-analysis. With regard to the subsequent development of ACVE following initiation on the different dialysis modalities, the pooled RR was found to be non-significant. Peritoneal dialysis is a suitable and cost-effective alternative to HD for ESRD patients at risk of cardiovascular disease.

Disease Monitoring Using Post-induction Circulating Tumor DNA Analysis Following First-Line Therapy in Patients with Metastatic Colorectal Cancer

PURPOSE

We assessed plasma circulating tumor DNA (ctDNA) level as a prognostic marker for progression-free survival (PFS) following first-line metastatic colorectal cancer (mCRC) therapy.

EXPERIMENTAL DESIGN

The Sequencing Triplet With Avastin and Maintenance (STEAM) was a randomized, phase II trial investigating efficacy of bevacizumab (BEV) plus 5-fluorouracil/leucovorin/oxaliplatin (FOLFOX) and 5-fluorouracil/leucovorin/irinotecan (FOLFIRI), administered concurrently or sequentially, versus FOLFOX-BEV in first-line mCRC. Evaluation of biomarkers associated with treatment outcomes was an exploratory endpoint. Patients in the biomarker-evaluable population (BEP) had 1 tissue sample, 1 pre-induction plasma sample, and 1 post-induction plasma sample collected ≤60 days of induction from last drug date.

RESULTS

Among the 280 patients enrolled in STEAM, 183 had sequenced and evaluable tumor tissue, 118 had matched pre-induction plasma, and 54 (BEP) had ctDNA-evaluable sequencing data for pre- and post-induction plasma. The most common somatic variants in tumor tissue and pre-induction plasma were TP53, APC, and KRAS. Patients with lower-than-median versus higher-than-median post-induction mean allele fraction (mAF) levels had longer median PFS (17.7 vs. 7.5 months, HR, 0.33; 95% confidence interval, 0.17-0.63). Higher levels of post-induction mAF and post-induction mean mutant molecules per milliliter (mMMPM), and changes in ctDNA (stratified by a 10-fold or 100-fold reduction in mAF between pre- and post-induction plasma), were associated with shorter PFS. Post-induction mAF and mMMPM generally correlated with each other (ρ = 0.987, P < 0.0001).

CONCLUSIONS

ctDNA quantification in post-induction plasma may serve as a prognostic biomarker for mCRC post-treatment outcomes.

Weekly paclitaxel, carboplatin, cetuximab, and cetuximab, docetaxel, cisplatin, and fluorouracil, followed by local therapy in previously untreated, locally advanced head and neck squamous cell carcinoma

BACKGROUND

The survival advantage of induction chemotherapy (IC) followed by locoregional treatment is controversial in locally advanced head and neck squamous cell carcinoma (LAHNSCC). We previously showed feasibility and safety of cetuximab-based IC (paclitaxel/carboplatin/cetuximab-PCC, and docetaxel/cisplatin/5-fluorouracil/cetuximab-C-TPF) followed by local therapy in LAHNSCC. The primary end point of this phase II clinical trial with randomization to PCC and C-TPF followed by combined local therapy in patients with LAHNSCC stratified by human papillomavirus (HPV) status and T-stage was 2-year progression-free survival (PFS) compared with historical control.

PATIENTS AND METHODS

Eligible patients were ≥18 years with squamous cell carcinoma of the oropharynx, oral cavity, nasopharynx, hypopharynx, or larynx with measurable stage IV (T0-4N2b-2c/3M0) and known HPV by p16 status. Stratification was by HPV and T-stage into one of the two risk groups: (i) low-risk: HPV-positive and T0-3 or HPV-negative and T0-2; (ii) intermediate/high-risk: HPV-positive and T4 or HPV-negative and T3-4. Patient reported outcomes were carried out.

RESULTS

A total of 136 patients were randomized in the study, 68 to each arm. With a median follow up of 3.2 years, the 2-year PFS in the PCC arm was 89% in the overall, 96% in the low-risk and 67% in the intermediate/high-risk groups; in the C-TPF arm 2-year PFS was 88% in the overall, 88% in the low-risk and 89% in the intermediate/high-risk groups.

CONCLUSION

The observed 2-year PFS of PCC in the low-risk group and of C-TPF in the intermediate/high-risk group showed a 20% improvement compared with the historical control derived from RTOG-0129, therefore reaching the primary end point of the trial.

Single-Cell Analysis of the Periodontal Immune Niche in Type 2 Diabetes

Periodontitis (PD) is a common source of uncontrolled inflammation in obesity-associated type 2 diabetes (T2D). PD apparently fuels the inflammation of T2D and associates with poor glycemic control and increased T2D morbidity. New therapeutics are critically needed to counter the sources of periodontal infection and inflammation that are accelerated in people with T2D. The precise mechanisms underlying the relationship between PD and T2D remain poorly understood. Every major immune cell subset has been implicated in the unresolved inflammation of PD, regardless of host metabolic health. However, analyses of inflammatory cells in PD with human periodontal tissue have generally focused on mRNA quantification and immunohistochemical analyses, both of which provide limited information on immune cell function. We used a combination of flow cytometry for cell surface markers and enzyme-linked immunospot methods to assess the subset distribution and function of immune cells isolated from gingiva of people who had PD and were systemically healthy, had PD and T2D (PD/T2D), or, for flow cytometry, were systemically and orally healthy. T-cell subsets dominated the cellular immune compartment in gingiva from all groups, and B cells were relatively rare. Although immune cell frequencies were similar among groups, a higher proportion of CD11b⁺ or CD4⁺ cells secreted IFNγ/IL-10 or IL-8, respectively, in cells from PD/T2D samples as compared with PD-alone samples. Our data indicate that fundamental differences in gingival immune cell function between PD and T2D-potentiated PD may account for the increased risk and severity of PD in subjects with T2D. Such differences may suggest unexpected therapeutic targets for alleviating periodontal inflammation in people with T2D.

Thromboembolic Outcomes of Different Anticoagulation Strategies for Patients with Atrial Fibrillation in the Setting of Hypertrophic Cardiomyopathy: A Systematic Review

Objective

Limited data is available assessing the efficacy and safety of different anticoagulation (AC) strategies for prevention of thromboembolic events, major bleeding, and all-cause mortality in patients with hypertrophic cardiomyopathy (HCM) and atrial fibrillation (AF). In this systematic review, we conducted a literature search to examine the possible association between different AC strategies and prevention of these adverse outcomes.

Methods

Scientific databases (PubMed, EMBASE, and Scopus) were searched using relevant medical subject headings and keywords to retrieve studies published through September of 2019. Studies assessing the outcomes of interest in patients with HCM and AF receiving AC, no AC as well as direct oral anticoagulants (DOACs) and vitamin K antagonists (VKAs) were selected.

Results

This review identified 14 observational studies evaluating thromboembolic events by AC strategies in 8,479 participants with concomitant HCM and AF. The use of AC was associated with a lower pooled incidence rate of total thromboembolic events at 9.5% (112 events in 1,175 patients) compared to 22.1% with no AC (108 events in 489 patients). In addition, the use of DOACs was associated with a lower pooled incidence rate of thromboembolic events at 4.7% (169 events in 3,576 patients) compared to 8.7% with VKAs (281 events in 3,239 patients). Furthermore, the use of DOACs compared to VKAs was associated with a lower pooled incidence rate of major bleeding and all-cause mortality at 3.8% (136 events in 3,576 patients) versus 6.8% (220 events in 3,239 patients) and 4.1% (124 events in 3,008 patients) versus 16.1% (384 events in 2,380 patients), respectively.

Conclusions

AC of patients with concomitant HCM and AF was associated with a lower incidence of thromboembolic events when compared to antiplatelet therapy or no treatment. Treatment with DOACs was also associated with a lower incidence of thromboembolic events, major bleeding, and all-cause mortality when compared to VKAs.

Quantitative positron emission tomography reveals regional differences in aerobic glycolysis within the human brain

Glucose and oxygen metabolism are tightly coupled in the human brain, with the preponderance of the brain's glucose supply used to generate ATP via oxidative phosphorylation. A fraction of glucose is consumed outside of oxidative phosphorylation despite the presence of sufficient oxygen to do so. We refer to this process as aerobic glycolysis. A recent positron emission tomography study reported that aerobic glycolysis is uniform within gray matter. Here, we analyze the same data and demonstrate robust regional differences in aerobic glycolysis within gray matter, a finding consistent with previously published data.

Suppressed immune microenvironment and repertoire in brain metastases from patients with resected non-small-cell lung cancer

BACKGROUND

The tumor immune microenvironment (TIME) of lung cancer brain metastasis is largely unexplored. We carried out immune profiling and sequencing analysis of paired resected primary tumors and brain metastases of non-small-cell lung carcinoma (NSCLC).

PATIENTS AND METHODS

TIME profiling of archival formalin-fixed and paraffin-embedded specimens of paired primary tumors and brain metastases from 39 patients with surgically resected NSCLCs was carried out using a 770 immune gene expression panel and by T-cell receptor beta repertoire (TCRβ) sequencing. Immunohistochemistry was carried out for validation. Targeted sequencing was carried out to catalog hot spot mutations in cancer genes.

RESULTS

Somatic hot spot mutations were mostly shared between both tumor sites (28/39 patients; 71%). We identified 161 differentially expressed genes, indicating inhibition of dendritic cell maturation, Th1, and leukocyte extravasation signaling pathways, in brain metastases compared with primary tumors (P < 0.01). The proinflammatory cell adhesion molecule vascular cell adhesion protein 1 was significantly suppressed in brain metastases compared with primary tumors. Brain metastases exhibited lower T cell and elevated macrophage infiltration compared with primary tumors (P < 0.001). T-cell clones were expanded in 64% of brain metastases compared with their corresponding primary tumors. Furthermore, while TCR repertoires were largely shared between paired brain metastases and primary tumors, T-cell densities were sparse in the metastases.

CONCLUSION

We present findings that suggest that the TIME in brain metastases from NSCLC is immunosuppressed and comprises immune phenotypes (e.g. immunosuppressive tumor-associated macrophages) that may help guide immunotherapeutic strategies for NSCLC brain metastases.

Bone mineral density as a dose-response predictor for osteoporosis: a propensity score analysis of longitudinal incident study (KCIS no. 39)

BACKGROUND

Osteoporosis is a global disease burden for aging society. The role of quantitative ultrasound (QUS) in the prediction for osteoporosis in a dose-response manner is hardly addressed.

AIM

We aimed to show the dose-response of QUS measurement in the prediction for osteoporosis by a community-based study.

DESIGN

A prospective cohort study.

METHODS

Participants were recruited between 2000 and 2004. Demographic data and heel QUS measurement were collected at baseline. Diagnosis of osteoporosis was ascertained by the follow-up of this cohort over time. In order to reduce the imbalance of baseline characteristics in the observational study, we applied propensity score by using proportional odds regression analysis to match the quintiles of QUS T-score.

RESULTS

A total of 44 957 subjects composed of 17 678 men (39.3%) and 27 279 women (69.7%) were recruited. After adjustments for propensity score, an increase in one unit of QUB T-score led to 7% reduction in the risk for osteoporosis [adjusted odds ratio (OR) = 0.93, 95% confidence interval (CI): 0.89-0.96, P < 0.0001]. Higher quintile of QUS T-score yielded a lower risk of osteoporosis with a gradient relationship [OR: 0.82 (95%CI: 0.72-0.92); OR: 0.81 (95%CI: 0.71-0.91); OR: 0.77 (95%CI: 0.68-0.87) and OR: 0.76 (95%CI: 0.67-0.86)] from the second to highest quintile opposed to first quintile (P < 0.0001). The cumulative incidence of osteoporosis was higher in the lower quintile during follow-up (log-rank test, P < 0.001).

CONCLUSION

QUS is an independent predictor for osteoporosis in a dose-response manner using a large population-based cohort. Due to the lower cost and portability of QUS measurement, the pre-screening for osteoporosis by QUS can be considered in the area with limited resources can be a feasible and alternative method.

Practical administration of intravenous contrast media in children: screening, prophylaxis, administration and treatment of adverse reactions

Administration of intravenous contrast media to children is a routine practice at many clinical imaging centers, that can involve special considerations. In this paper, we provide practical information to facilitate optimal performance and oversight of this task. We provide targeted screening questions that can help to identify high-risk pediatric patients for both iodine-based and gadolinium-based intravenous contrast media administration. These include children at risk for allergic-like reactions, thyroid dysfunction, contrast-induced nephropathy, and nephrogenic systemic fibrosis. We make recommendations for addressing "yes" responses to screening questions using risk stratification schema that are specific to children. We also present criteria for selecting children for premedication prior to intravenous contrast administration, and suggest pediatric regimens. Additionally, we discuss practical nuances of intravenous contrast media administration to children and provide a quick-reference table of appropriate treatments with pediatric dosages for adverse contrast reactions.

Levo-transposition of the Great Arteries in an Adult Patient: Management Considerations and Treatment Strategy

Levo-transposition of the great arteries (L-TGA) is a rare congenital heart anomaly associated with the increased risk of developing heart failure (HF) as well as complete heart block at a young age. Due to limited data regarding the treatment strategy in the adult L-TGA sub-population, shared medical decision-making should occur between the patient and a team of physicians. Clinical status, age, and associated cardiac lesions or rhythm disturbances can affect patient outcomes. These factors should be considered prior to pursuing a surgical versus a medicinal approach.