Infective endocarditis associated with left atrial appendage occlusion device: a contemporary systematic review.

BACKGROUND: Data are limited regarding infective endocarditis (IE) complicating left atrial appendage occlusion (LAAO) device procedures. This systematic review examines the etiology, diagnosis, and management of infective endocarditis (IE) following LAAO. METHODS: A comprehensive search of six databases was performed between 2007 and 2022. In selecting studies, articles were included if they provided information about IE complicating LAAO, with relevant clinical and imaging details. Articles were excluded if they were editorials, study protocols, letters, or abstracts. RESULTS: We identified seven cases of IE complicating LAAO published between 2007 and 2022, from the United States and Europe, highlighting the exceedingly rare reported incidence of the condition. Staphylococcus aureus is the predominant organism implicated in LAAO infections. Echocardiography is a key imaging modality for diagnosing LAAO IE. Both antibiotic therapy and surgical intervention in appropriate patients are important for managing LAAO device-related IE. CONCLUSIONS: The limited data in the current literature regarding LAAO IE underscores the need for prospective clinical trials to establish evidence-based guidelines for infection prophylaxis, diagnosis, and management. Our findings emphasize the importance of vigilance for device-related infections, especially as the use of LAAO devices continues to grow worldwide.

Does consensus contour improve robustness and accuracy in 18F-FDG PET radiomic features?

PURPOSE: The purpose of our study is to validate the robustness and accuracy of consensus contour in 2-deoxy-2-[ 18 F]fluoro-D-glucose ( 18 F-FDG) PET radiomic features. METHODS: 225 nasopharyngeal carcinoma (NPC) and 13 extended cardio-torso (XCAT) simulated data were enrolled. All segmentation were performed with four segmentation methods under two different initial masks, respectively. Consensus contour (ConSeg) was then developed using the majority vote rule. 107 radiomic features were extracted by Pyradiomics based on segmentation and the intraclass correlation coefficient (ICC) was calculated for each feature between masks or among segmentation, respectively. In XCAT ICC between segmentation and simulated ground truth were also calculated to access the accuracy. RESULTS: ICC varied with the dataset, segmentation method, initial mask and feature type. ConSeg presented higher ICC for radiomic features in robustness tests and similar ICC in accuracy tests, compared with the average of four segmentation results. Higher ICC were also generally observed in irregular initial masks compared with rectangular masks in both robustness and accuracy tests. Furthermore, 19 features (17.76%) had ICC ≥ 0.75 in both robustness and accuracy tests for any of the segmentation methods or initial masks. The dataset was observed to have a large impact on the correlation relationships between radiomic features, but not the segmentation method or initial mask. CONCLUSIONS: The consensus contour combined with irregular initial mask could improve the robustness and accuracy in radiomic analysis to some extent. The correlation relationships between radiomic features and feature clusters largely depended on the dataset, but not segmentation method or initial mask.

Predicting FDG-PET Images From Multi-Contrast MRI Using Deep Learning in Patients With Brain Neoplasms.

BACKGROUND: 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determining presence of viable tumor, but is limited by geographical restrictions, radiation exposure, and high cost. PURPOSE: To generate diagnostic-quality PET equivalent imaging for patients with brain neoplasms by deep learning with multi-contrast MRI. STUDY TYPE: Retrospective. SUBJECTS: Patients (59 studies from 51 subjects; age 56 ± 13 years; 29 males) who underwent 18 F-FDG PET and MRI for determining recurrent brain tumor. FIELD STRENGTH/SEQUENCE: 3T; 3D GRE T1, 3D GRE T1c, 3D FSE T2-FLAIR, and 3D FSE ASL, 18 F-FDG PET imaging. ASSESSMENT: Convolutional neural networks were trained using four MRIs as inputs and acquired FDG PET images as output. The agreement between the acquired and synthesized PET was evaluated by quality metrics and Bland-Altman plots for standardized uptake value ratio. Three physicians scored image quality on a 5-point scale, with score ≥3 as high-quality. They assessed the lesions on a 5-point scale, which was binarized to analyze diagnostic consistency of the synthesized PET compared to the acquired PET. STATISTICAL TESTS: The agreement in ratings between the acquired and synthesized PET were tested with Gwet's AC and exact Bowker test of symmetry. Agreement of the readers was assessed by Gwet's AC. P = 0.05 was used as the cutoff for statistical significance. RESULTS: The synthesized PET visually resembled the acquired PET and showed significant improvement in quality metrics (+21.7% on PSNR, +22.2% on SSIM, -31.8% on RSME) compared with ASL. A total of 49.7% of the synthesized PET were considered as high-quality compared to 73.4% of the acquired PET which was statistically significant, but with distinct variability between readers. For the positive/negative lesion assessment, the synthesized PET had an accuracy of 87% but had a tendency to overcall. CONCLUSION: The proposed deep learning model has the potential of synthesizing diagnostic quality FDG PET images without the use of radiotracers. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Does consensus contours improve robustness and accuracy on [Formula: see text]F-FDG PET imaging tumor delineation?

PURPOSE: The aim of this study is to explore the robustness and accuracy of consensus contours with 225 nasopharyngeal carcinoma (NPC) clinical cases and 13 extended cardio-torso simulated lung tumors (XCAT) based on 2-deoxy-2-[[Formula: see text]F]fluoro-D-glucose ([Formula: see text]F-FDG) PET imaging. METHODS: Primary tumor segmentation was performed with two different initial masks on 225 NPC [Formula: see text]F-FDG PET datasets and 13 XCAT simulations using methods of automatic segmentation with active contour, affinity propagation (AP), contrast-oriented thresholding (ST), and 41% maximum tumor value (41MAX), respectively. Consensus contours (ConSeg) were subsequently generated based on the majority vote rule. The metabolically active tumor volume (MATV), relative volume error (RE), Dice similarity coefficient (DSC) and their respective test-retest (TRT) metrics between different masks were adopted to analyze the results quantitatively. The nonparametric Friedman and post hoc Wilcoxon tests with Bonferroni adjustment for multiple comparisons were performed with [Formula: see text] 0.05 considered to be significant. RESULTS: AP presented the highest variability for MATV in different masks, and ConSeg presented much better TRT performances in MATV compared with AP, and slightly poorer TRT in MATV compared with ST or 41MAXin most cases. Similar trends were also found in RE and DSC with the simulated data. The average of four segmentation results (AveSeg) showed better or comparable results in accuracy for most cases with respect to ConSeg. AP, AveSeg and ConSeg presented better RE and DSC in irregular masks as compared with rectangle masks. Additionally, all methods underestimated the tumour boundaries in relation to the ground truth for XCAT including respiratory motion. CONCLUSIONS: The consensus method could be a robust approach to alleviate segmentation variabilities, but did not seem to improve the accuracy of segmentation results on average. Irregular initial masks might be at least in some cases attributable to mitigate the segmentation variability as well.

Insights into Insulin Resistance and Calcification in the Myocardium in Type 2 Diabetes: A Coronary Artery Analysis.

Type 2 diabetes (T2D) is responsible for high incidence of cardiovascular (CV) complications leading to heart failure. Coronary artery region-specific metabolic and structural assessment could provide deeper insight into the extent of the disease and help prevent adverse cardiac events. Therefore, in this study, we aimed at investigating such myocardial dynamics for the first time in insulin-sensitive (mIS) and insulin-resistant (mIR) T2D patients. We targeted global and region-specific variations using insulin sensitivity (IS) and coronary artery calcifications (CACs) as CV risk factor in T2D patients. IS was computed using myocardial segmentation approaches at both baseline and after an hyperglycemic-insulinemic clamp (HEC) on [18F]FDG-PET images using the standardized uptake value (SUV) (ΔSUV = SUVHEC - SUVBASELINE) and calcifications using CT Calcium Scoring. Results suggest that some communicating pathways between response to insulin and calcification are present in the myocardium, whilst differences between coronary arteries were only observed in the mIS cohort. Risk indicators were mostly observed for mIR and highly calcified subjects, which supports previously stated findings that exhibit a distinguished exposure depending on the impairment of response to insulin, while projecting added potential complications due to arterial obstruction. Moreover, a pattern relating calcification and T2D phenotypes was observed suggesting the avoidance of insulin treatment in mIS but its endorsement in mIR subjects. The right coronary artery displayed more ΔSUV, whilst plaque was more present in the circumflex. However, differences between phenotypes, and therefore CV risk, were associated to left descending artery (LAD) translating into higher CACs regarding IR, which could explain why insulin treatment was effective for LAD at the expense of higher likelihood of plaque accumulation. Personalized approaches to assess T2D may lead to more efficient treatments and risk-prevention strategies.

Propolis induces cardiac metabolism changes in 6-hydroxydopamine animal model: A dietary intervention as a potential cardioprotective approach in Parkinson's disease.

While there is sustained growth of the older population worldwide, ageing is a consistent risk factor for neurodegenerative diseases, such as Parkinson's-disease (PD). Considered an emblematic movement disorder, PD comprises a miscellany of non-motor symptoms, for which effective management remains an unfulfilled need in clinical practice. Highlighted are the cardiovascular abnormalities, that cause significant burden in PD patients. Evidence suggests that key biological processes underlying PD pathophysiology can be modulated by diet-derived bioactive compounds, such as green propolis, a natural functional food with biological and pharmacological properties. The effects of propolis on cardiac affection associated to PD have received little coverage. In this study, a metabolomics approach and Positron Emission Tomography (PET) imaging were used to assess the metabolic response to diet supplementation with green propolis on heart outcomes of rats with Parkinsonism induced by 6-hydroxydopamine (6-OHDA rats). Untargeted metabolomics approach revealed four cardiac metabolites (2-hydroxybutyric acid, 3-hydroxybutyric acid, monoacylglycerol and alanine) that were significantly modified between animal groups (6-OHDA, 6-OHDA + Propolis and sham). Propolis-induced changes in the level of these cardiac metabolites suggest beneficial effects of diet intervention. From the metabolites affected, functional analysis identified changes in propanoate metabolism (a key carbohydrate metabolism related metabolic pathway), glucose-alanine cycle, protein and fatty acid biosynthesis, energy metabolism, glutathione metabolism and urea cycle. PET imaging detected higher glucose metabolism in the 17 areas of the left ventricle of all rats treated with propolis, substantially contrasting from those rats that did not consume propolis. Our results bring new insights into cardiac metabolic substrates and pathways involved in the mechanisms of the effects of propolis in experimental PD and provide potential novel targets for research in the quest for future therapeutic strategies.

Surveillance tools for detection of recurrent nasopharyngeal carcinoma: An evidence-based review and recommendations.

Objective: Nasopharyngeal carcinomas (NPC) are tumors arising from epithelium of the nasopharynx. The 5-year survival rate of primary NPC is 80% with significant risks of recurrence. The objective here is to provide an evidence-based systemic review of the diagnostic value of different modalities in detecting local, regional, and distal recurrent NPC, as well as the associated costs with these modalities. Methods: MEDLINE, EMBASE, and the Cochrane review database were queried. Two hundred and twenty-three abstracts were generated using the inclusion criteria: patients >18 years of age; histopathological reference standard; and modalities pertaining to imaging or microbiology. Results: Twenty-four manuscripts fulfilled the inclusion criteria and 5 surveillance tools identified: endoscopy, MR, FDG-PET, Tc-99m MIBI and 201TI SPECT, and EBV DNA. Conclusions: For local surveillance, endoscopy is the gold standard recommendation, with increased efficacy if Narrow Band Imaging or contact endoscopy are utilized. MRI and FDG-PET is also recommended to help with local to distal spread; however, Tc-99m MIBI and 201TI SPECT are options as well. EBV DNA is recommended as a cheap and accessible adjunct surveillance tool if an available as an option.

Synthetic 18F-FDG PET Image Generation Using a Combination of Biomathematical Modeling and Machine Learning.

No previous works have attempted to combine generative adversarial network (GAN) architectures and the biomathematical modeling of positron emission tomography (PET) radiotracer uptake in tumors to generate extra training samples. Here, we developed a novel computational model to produce synthetic 18F-fluorodeoxyglucose (18F-FDG) PET images of solid tumors in different stages of progression and angiogenesis. First, a comprehensive biomathematical model is employed for creating tumor-induced angiogenesis, intravascular and extravascular fluid flow, as well as modeling of the transport phenomena and reaction processes of 18F-FDG in a tumor microenvironment. Then, a deep convolutional GAN (DCGAN) model is employed for producing synthetic PET images using 170 input images of 18F-FDG uptake in each of 10 different tumor microvascular networks. The interstitial fluid parameters and spatiotemporal distribution of 18F-FDG uptake in tumor and healthy tissues have been compared against previously published numerical and experimental studies, indicating the accuracy of the model. The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the generated PET sample and the experimental one are 0.72 and 28.53, respectively. Our results demonstrate that a combination of biomathematical modeling and GAN-based augmentation models provides a robust framework for the non-invasive and accurate generation of synthetic PET images of solid tumors in different stages.

Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography.

In animal experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure is crucial. However, an accurate assessment method based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is still lacking. The difficulty lies in the inconsistent preprocessing pipeline, biased intensity normalization, or unclear spatiotemporal uptake of FDG. Here, we propose an image feature-based protocol to assess the quality of the procedure using a 3D scale-invariant feature transform and support vector machine. This feature-based protocol provides a convenient, accurate, and reliable tool to assess the quality of the MCAO procedure in FDG PET studies. Compared with existing approaches, the proposed protocol is fully quantitative, objective, automatic, and bypasses the intensity normalization step. An online interface was constructed to check images and obtain assessment results.

Age-related reduction of hemispheric asymmetry by pigeons: A behavioral and FDG-PET imaging investigation of visual discrimination.

Pigeons are long-lived and slowly aging animals that present a distinct opportunity to further our understanding of age-related brain changes. Generally, for pigeons, the left hemisphere contributes to discrimination of local information, whereas the right contributes to processing of global information. The function of each hemisphere may be examined by covering one eye, as the optic nerves decussate almost completely in birds, directing the majority of visual information to the contralateral hemisphere. Using this eye-capping technique, we investigated pigeons' ability to select grains from among grit while under binocular and monocular viewing conditions, across three different age groups. Prior to the grit-grain discrimination task, pigeons were injected with a radioactive tracer, which was taken up by the brain as the pigeons performed the task. Upon completion of the discrimination task, the pigeons' brains were imaged via [18F] fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This process allowed us to compare hemispheric activity during the discrimination task for each individual within each age group. The Very Old subjects showed significantly worse discrimination performance compared to the Adult and Old subjects, particularly when needing to search primarily with their right hemisphere. Furthermore, the Very Old subjects did not show differences in hemispheric activation when performing the task, whereas the left hemisphere was most active for the Adult and Old groups. To our knowledge, this is the first study to use FDG-PET imaging to evaluate whether the pigeon brain shows evidence of age-related reduction in hemispheric asymmetry during a visual discrimination task.

Cannabidiol Treatment Improves Glucose Metabolism and Memory in Streptozotocin-Induced Alzheimer's Disease Rat Model: A Proof-of-Concept Study.

An early and persistent sign of Alzheimer's disease (AD) is glucose hypometabolism, which can be evaluated by positron emission tomography (PET) with 18F-2-fluoro-2-deoxy-D-glucose ([18F]FDG). Cannabidiol has demonstrated neuroprotective and anti-inflammatory properties but has not been evaluated by PET imaging in an AD model. Intracerebroventricular (icv) injection of streptozotocin (STZ) is a validated model for hypometabolism observed in AD. This proof-of-concept study evaluated the effect of cannabidiol treatment in the brain glucose metabolism of an icv-STZ AD model by PET imaging. Wistar male rats received 3 mg/kg of STZ and [18F]FDG PET images were acquired before and 7 days after STZ injection. Animals were treated with intraperitoneal cannabidiol (20 mg/kg-STZ-cannabidiol) or saline (STZ-saline) for one week. Novel object recognition was performed to evaluate short-term and long-term memory. [18F]FDG uptake in the whole brain was significantly lower in the STZ-saline group. Voxel-based analysis revealed a hypometabolism cluster close to the lateral ventricle, which was smaller in STZ-cannabidiol animals. The brain regions with more evident hypometabolism were the striatum, motor cortex, hippocampus, and thalamus, which was not observed in STZ-cannabidiol animals. In addition, STZ-cannabidiol animals revealed no changes in memory index. Thus, this study suggests that cannabidiol could be an early treatment for the neurodegenerative process observed in AD.

Aceruloplasminemia: a multimodal imaging study in an Italian family with a novel mutation.

OBJECTIVE: Structural abnormalities in thalami and basal ganglia, in particular the globus pallidus (GP), are a neuroimaging hallmark of hereditary aceruloplasminemia (HA), yet few functional imaging data exit in HA carriers. This study investigated the iron-related structural and functional abnormalities in an Italian HA family. METHODS: Multimodal imaging was used including structural 3 T MRI, functional imaging (SPECT imaging with 123I-ioflupane (DAT-SPECT), cardiac 123I metaiodobenzylguanidine (123I-MIBG) scintigraphy, and 18F-fluorodeoxyglucose (18F-FDG)-PET imaging). In the proband, MRI and scintigraphic evaluations were performed at baseline, 2 and 4 years (structural imaging), and 2 years of follow-up period (functional imaging). RESULTS: We investigated two cousins carrying a novel splicing homozygous mutation in intron 6 (IVS6 + 1 G > A) of CP gene. Interestingly, MRI features in both subjects were characterized by marked iron accumulation in the thalami and basal ganglia nuclei, while GP was not affected. MRI performed in the proband at 2 and 4 years of follow-up confirmed progressive neurodegeneration of the thalami and basal ganglia without the involvement of GP. Functional imaging showed reduced putaminal DAT uptake in both cousins, whereas cardiac MIBG and FDG uptakes performed in the proband were normal. Longitudinal scintigraphic investigations did not show significant changes over the time. CONCLUSIONS: For HA carriers, our findings demonstrate that GP was spared by iron accumulation over the time. The nigrostriatal presynaptic dopaminergic system was damaged while the cardiac sympathetic system remained longitudinally preserved, thus expanding the imaging features of this rare inherited disorder.

Metabolic Scar Assessment with18F-FDG PET: Correlation to Ischemic Ventricular Tachycardia Substrate and Successful Ablation Sites.

The functional and molecular imaging characteristics of ischemic ventricular tachycardia (VT) substrate are incompletely understood. Our objective was to compare regional 18F-FDG PET tracer uptake with detailed electroanatomic maps (EAMs) in a more extensive series of postinfarction VT patients to define the metabolic properties of VT substrate and successful ablation sites. Methods: Three-dimensional (3D) metabolic left ventricular reconstructions were created from perfusion-normalized 18F-FDG PET images in consecutive patients undergoing VT ablation. PET defects were classified as severe (defined as <50% uptake) or moderate (defined as 50%-70% uptake), as referenced to the maximal 17-segment uptake. Color-coded PET scar reconstructions were coregistered with corresponding high-resolution 3D EAMs, which were classified as indicating dense scarring (defined as voltage < 0.5 mV), normal myocardium (defined as voltage > 1.5 mV), or border zones (defined as voltage of 0.5-1.5 mV). Results: All 56 patients had ischemic cardiomyopathy (ejection fraction, 29% ± 12%). Severe PET defects were larger than dense scarring, at 63.0 ± 48.4 cm2 versus 13.8 ± 33.1 cm2 (P < 0.001). Similarly, moderate/severe PET defects (≤70%) were larger than areas with abnormal voltage (≤1.5 mV) measuring 105.1 ± 67.2 cm2 versus 56.2 ± 62.6 cm2 (P < 0.001). Analysis of bipolar voltage (23,389 mapping points) showed decreased voltage among severe PET defects (n = 10,364; 0.5 ± 0.3 mV) and moderate PET defects (n = 5,243; 1.5 ± 0.9 mV, P < 0.01), with normal voltage among normal PET areas (>70% uptake) (n = 7,782, 3.2 ± 1.3 mV, P < 0.001). Eighty-eight percent of VT channel or exit sites (n = 44) were metabolically abnormal (severe PET defect, 78%; moderate PET defect, 10%), whereas 12% (n = 6) were in PET-normal areas. Metabolic channels (n = 26) existed in 45% (n = 25) of patients, with an average length and width of 17.6 ± 12.5 mm and 10.3 ± 4.2 mm, respectively. Metabolic channels were oriented predominantly in the apex or base (86%), harboring VT channel or exit sites in 31%. Metabolic rapid-transition areas (>50% change in 18F-FDG tracer uptake/15 mm) were detected in 59% of cases (n = 33), colocalizing to VT channels or exit sites (15%) or near these sites (85%, 12.8 ± 8.5 mm). Metabolism-voltage mismatches in which there was a severe PET defect but voltage indicating normal myocardium were seen in 21% of patients (n = 12), 41% of whom were harboring VT channel or exit sites. Conclusion: Abnormal 18F-FDG uptake categories could be detected using incremental 3D step-up reconstructions. They predicted decreasing bipolar voltages and VT channel or exit sites in about 90% of cases. Additionally, functional imaging allowed detection of novel molecular tissue characteristics within the ischemic VT substrate such as metabolic channels, rapid-transition areas, and metabolism-voltage mismatches demonstrating intrasubstrate heterogeneity and providing possible targets for imaging-guided ablation.

18F-FDG PET imaging-monitored anti-inflammatory therapy for acute myocardial infarction: Exploring the role of MCC950 in murine model.

BACKGROUND: MCC950 is a novel NLRP3 inflammasome inhibitor that possesses potent anti-inflammatory properties in acute myocardial infarction (AMI). However, the lack of noninvasive monitoring methods limits its potential clinical translation. Thus, we sought to investigate whether 18F-FDG PET imaging can monitor the therapeutic effects of MCC950 in an AMI murine model. METHODS: C57BL/6 mice were used to generate an AMI model. MCC950 or sterile saline was intraperitoneally administered 1 hour after surgery and then daily for 7 consecutive days. 18F-FDG PET (inflammation) imaging was used to monitor inflammatory changes on days 3 and 5. Immunohistochemistry and Western blot were used to detect inflammatory markers and to confirm the PET imaging results. 18F-FDG PET (viability) imaging was used to quantitate the viability defect expansion on days 7 and 28. Cardiac ultrasound and survival analyses were performed to evaluate the cardiac function and survival rate. Adverse remodeling was determined by Wheat Germ Agglutinin (WGA) and Masson trichrome staining. RESULTS: The FDG-PET (inflammation) imaging revealed that MCC950 treatment led to lower 18F-FDG inflammatory uptakes, at the infarct region, on days 3 and 5 when compared to the MI group. The decreased M1 macrophages and neutrophils infiltration and the remission of the NLRP3/IL-1ß pathway, confirmed the FDG-PET (inflammation) imaging results. The FDG-PET (viability) imaging revealed that MCC950 significantly decreased the expansion of the viability defect, demonstrating its myocardial preservation effects. The acute FDG-PET (inflammation) signal positively correlated with the late viability defect and with the reduction in the left ventricular ejection fraction (LVEF). Additionally, the alleviated adverse remodeling and the improved survival rate further support the anti-inflammatory efficiency of MCC950 in AMI. CONCLUSION: Using 18F-FDG PET imaging, we noninvasively demonstrated the therapeutic effects of MCC950 in AMI and showed that 18F-FDG PET imaging holds promising application potentials in MCC950's clinical translation.

Metabolic lesion-deficit mapping of human cognition.

In theory the most powerful technique for functional localization in cognitive neuroscience, lesion-deficit mapping is in practice distorted by unmodelled network disconnections and strong 'parasitic' dependencies between collaterally damaged ischaemic areas. High-dimensional multivariate modelling can overcome these defects, but only at the cost of commonly impracticable data scales. Here we develop lesion-deficit mapping with metabolic lesions-discrete areas of hypometabolism typically seen on interictal 18F-fluorodeoxyglucose PET imaging in patients with focal epilepsy-that inherently capture disconnection effects, and whose structural dependence patterns are sufficiently benign to allow the derivation of robust functional anatomical maps with modest data. In this cross-sectional study of 159 patients with widely distributed focal cortical impairments, we derive lesion-deficit maps of a broad range of psychological subdomains underlying affect and cognition. We demonstrate the potential clinical utility of the approach in guiding therapeutic resection for focal epilepsy or other neurosurgical indications by applying high-dimensional modelling to predict out-of-sample verbal IQ and depression from cortical metabolism alone.

Hormonal Receptor Immunochemistry Heterogeneity and 18F-FDG Metabolic Heterogeneity: Preliminary Results of Their Relationship and Prognostic Value in Luminal Non-Metastatic Breast Cancers.

INTRODUCTION: We aimed to investigate whether 18F-FDG PET metabolic heterogeneity reflects the heterogeneity of estrogen receptor (ER) and progesterone receptor (PR) expressions within luminal non-metastatic breast tumors and if it could help in identifying patients with worst event-free survival (EFS). MATERIALS AND METHODS: On 38 PET high-resolution breast bed positions, a single physician drew volumes of interest encompassing the breast tumors to extract SUVmax, histogram parameters and textural features. High-resolution immunochemistry (IHC) scans were analyzed to extract Haralick parameters and descriptors of the distribution shape. Correlation between IHC and PET parameters were explored using Spearman tests. Variables of interest to predict the EFS status at 8 years (EFS-8y) were sought by means of a random forest classification. EFS-8y analyses were then performed using univariable Kaplan-Meier analyses and Cox regression analysis. When appropriate, Mann-Whitney tests and Spearman correlations were used to explore the relationship between clinical data and tumoral PET heterogeneity variables. RESULTS: For ER expression, correlations were mainly observed with 18F-FDG histogram parameters, whereas for PR expression correlations were mainly observed with gray-level co-occurrence matrix (GLCM) parameters. The strongest correlations were observed between skewness_ER and uniformity_HISTO (ρ = -0.386, p = 0.017) and correlation_PR and entropy_GLCM (ρ = 0.540, p = 0.001), respectively. The median follow-up was 6.5 years and the 8y-EFS was 71.0%. Random forest classification found age, clinical stage, SUVmax, skewness_ER, kurtosis_ER, entropy_HISTO, and uniformity_HISTO to be variables of importance to predict the 8y-EFS. Univariable Kaplan-Meier survival analyses showed that skewness_ER was a predictor of 8y-EFS (66.7 ± 27.2 versus 19.1 ± 15.2, p = 0.018 with a cut-off value set to 0.163) whereas other IHC and PET parameters were not. On multivariable analysis including age, clinical stage and skewness_ER, none of the parameters were independent predictors. Indeed, skewness_ER was significantly higher in youngest patients (ρ = -0.351, p = 0.031) and in clinical stage III tumors (p = 0.023). CONCLUSION: A heterogeneous distribution of ER within the tumor in IHC appeared as an EFS-8y prognosticator in luminal non-metastatic breast cancers. Interestingly, it appeared to be correlated with PET histogram parameters which could therefore become potential non-invasive prognosticator tools, provided these results are confirmed by further larger and prospective studies.

Adjusting gait step-by-step: Brain activation during split-belt treadmill walking.

When walking on a split-belt treadmill, where each leg is driven at a different speed, a temporary change is made to the typical steady-state walking pattern. The exact ways in which the brain controls these temporary changes to walking are still unknown. Ten young adults (23±3y) walked on a split-belt treadmill for 30 min on 2 separate occasions: tied-belt control with both belts at comfortable walking speed, and continuous adjustment where speed ratio between belts changed every 15 seconds. 18F-fluorodeoxyglucose (18FDG) positron emission tomography (PET) imaging measured whole brain glucose metabolism distribution, or activation, during each treadmill walking condition. The continuous adjustment condition, compared to the tied-belt control, was associated with increased activity of supplementary motor areas (SMA), posterior parietal cortex (PPC), anterior cingulate cortex and anterior lateral cerebellum, and decreased activity of posterior cingulate and medial prefrontal cortex. In addition, peak activation of the PPC, SMA and PFC were correlated with cadence and temporal gait variability. We propose that a "fine-tuning" network for human locomotion exists which includes brain areas for sensorimotor integration, motor planning and goal directed attention. These findings suggest that distinct regions govern the inherent flexibility of the human locomotor plan to maintain a successful and adjustable walking pattern.

Brain Network and Abnormal Hemispheric Asymmetry Analyses to Explore the Marginal Differences in Glucose Metabolic Distributions Among Alzheimer's Disease, Parkinson's Disease Dementia, and Lewy Body Dementia.

Facilitating accurate diagnosis and ensuring appropriate treatment of dementia subtypes, including Alzheimer's disease (AD), Parkinson's disease dementia (PDD), and Lewy body dementia (DLB), is clinically important. However, the differences in glucose metabolic distribution among these three dementia subtypes are minor, which can result in difficulties in diagnosis by visual assessment or traditional quantification methods. Here, we explored this issue using novel approaches, including brain network and abnormal hemispheric asymmetry analyses. We generated 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) images from patients with AD, PDD, and DLB, and healthy control (HC) subjects (n = 22, 18, 22, and 22, respectively) from Huashan hospital, Shanghai, China. Brain network properties were measured and between-group differences evaluated using graph theory. We also calculated and explored asymmetry indices for the cerebral hemispheres in the four groups, to explore whether differences between the two hemispheres were characteristic of each group. Our study revealed significant differences in the network properties of the HC and AD groups (small-world coefficient, 1.36 vs. 1.28; clustering coefficient, 1.48 vs. 1.59; characteristic path length, 1.57 vs. 1.64). In addition, differing hub regions were identified in the different dementias. We also identified rightward asymmetry in the hemispheric brain networks of patients with AD and DLB, and leftward asymmetry in the hemispheric brain networks of patients with PDD, which were attributable to aberrant topological properties in the corresponding hemispheres.

Aging alters glucose uptake in the naïve and injured rodent spinal cord.

Aging results in increased activation of inflammatory glial cells and decreased neuronal viability following spinal cord injury (SCI). Metabolism and transport of glucose is also decreased with age, although the influence of age on glucose transporter (GLUT) expression or glucose uptake in SCI is currently unknown. We therefore performed [18F]Fluorodeoxyglucose (FDG) PET imaging of young (3 month) and middle-aged (12 month) rats. Glucose uptake in middle-aged rats was decreased compared to young rats at baseline, followed by increased uptake 14 days post contusion SCI. qRT-PCR and protein analysis revealed an association between 14 day glucose uptake and 14 day post-injury inflammation. Further, gene expression analysis of neuron-specific GLUT3 and non-specific GLUT4 (present on glial cells) revealed an inverse relationship between GLUT3/4 gene expression and glucose uptake patterns. Protein expression revealed increased GLUT3 in 3 month rats only, consistent with age related decreases in glucose uptake, and increased GLUT4 in 12 month rats only, consistent with age related increases in inflammatory activity and glucose uptake. Inconsistencies between gene and protein suggest an influence of age-related impairment of translation and/or protein degradation. Overall, our findings show that age alters glucose uptake and GLUT3/4 expression profiles before and after SCI, which may be dependent on level of inflammatory response, and may suggest a therapeutic avenue in addressing glucose uptake in the aging population.