Association of serum 25-hydroxy-vitamin D concentration and risk of mortality in cancer survivors in the United States.

PURPOSE: Cancer survivors have a high risk of mortality, and vitamin D (VD) is associated with the risk of mortality. This study is aim to examine the impact of VD on mortality in cancer survivors. METHODS: A prospective study was conducted using data from the National Health and Nutrition Examination Survey. Participants were obtained information on their baseline characteristics, dietary habits, comorbidities, lifestyle, and serum 25-hydroxy VD [25(OH)D] concentrations. The weighted Cox proportional hazard and competing risk regression models were used to estimate the hazard ratio and 95% confidence intervals (HR, 95% CI) of mortality for different serum 25(OH)D concentrations. Restricted cubic spline (RCS) curves were utilized to illustrate the dose-response relationship between serum 25(OH)D concentrations and mortality. RESULTS: The study encompassed 2,495 participants with cancer diagnoses. Multivariate models indicated that, compared to serum 25(OH)D concentrations below 58.5 nmol/L, concentrations exceeding 81.6 nmol/L were associated with reduced HRs for all-cause mortality (HR = 0.70; 95% CI: 0.56-0.87), cardiovascular mortality (HR = 0.53; 95% CI: 0.32-0.86), and cancer-specific mortality (HR = 0.66; 95% CI: 0.45-0.99). RCS curves revealed "L-shaped" associations between serum 25(OH)D concentration and both all-cause and cancer-specific mortality, with threshold effects at 87.9 nmol/L and 84.6 nmol/L, respectively. Conversely, the relationship between serum 25(OH)D concentration and cardiovascular mortality exhibited a more linear pattern, with a threshold at 88.7 nmol/L. Subgroup analyses highlighted a gender-specific interaction that elevated serum 25(OH)D concentrations were significantly more protective against mortality in males than in females, especially regarding cancer-specific mortality (P-interaction = 0.009). CONCLUSION: Elevated serum 25(OH)D concentrations were correlated with decreased risks of all-cause, cardiovascular, and cancer-specific mortality in cancer survivors, with benefit thresholds at 87.9, 88.7, and 84.6 nmol/L, respectively. These findings suggested that cancer survivors might benefit from higher vitamin D recommendations than the general population.

Left Ventricular Remodelling Associated with the Transient Elevated [68Ga]Ga-Pentixafor Activity in the Remote Myocardium Following Acute Myocardial Infarction.

BACKGROUND: Previous studies have initially reported accompanying elevated 2-deoxy-2[18F]fluoro-D-glucose ([18F]F-FDG) inflammatory activity in the remote area and its prognostic value after acute myocardial infarction (AMI). Non-invasive characterization of the accompanying inflammation in the remote myocardium may be of potency in guiding future targeted theranostics. [68Ga]Ga-Pentixafor targeting chemokine receptor 4 (CXCR4) on the surface of inflammatory cells is currently one of the promising inflammatory imaging agents. In this study, we sought to focus on the longitudinal evolution of [68Ga]Ga-Pentixafor activities in the remote myocardium following AMI and its association with cardiac function. METHODS: Twelve AMI rats and six Sham rats serially underwent [68Ga]Ga-Pentixafor imaging at pre-operation, and 5, 7, 14 days post-operation. Maximum and mean standard uptake value (SUV) and target-to-background ratio (TBR) were assessed to indicate the uptake intensity. Gated [18F]F-FDG imaging and immunofluorescent staining were performed to obtain cardiac function and responses of pro-inflammatory and reparative macrophages, respectively. RESULTS: The uptake of [68Ga]Ga-Pentixafor in the infarcted myocardium peaked at day 5 (all P = 0.003), retained at day 7 (all P = 0.011), and recovered at day 14 after AMI (P > 0.05), paralleling with the rise-fall pro-inflammatory M1 macrophages (P < 0.05). Correlated with the peak activity in the infarct territory, [68Ga]Ga-Pentixafor uptake in the remote myocardium on day 5 early after AMI significantly increased (AMI vs. Sham: SUVmean, SUVmax, and TBRmean: all P < 0.05), and strongly correlated with contemporaneous EDV and/or ESV (SUVmean and TBRmean: both P < 0.05). The transitory remote activity recovered as of day 7 post-AMI (AMI vs. Sham: P > 0.05). CONCLUSIONS: Corresponding with the peaked [68Ga]Ga-Pentixafor activity in the infarcted myocardium, the activity in the remote region elevated accordingly and led to contemporaneous left ventricular remodelling early after AMI. Further studies are warranted to clarify its clinical application potential.

Association of epicardial fat volume with subclinical myocardial damage in patients with type 2 diabetes mellitus.

Background: In type 2 diabetes mellitus (T2DM) patients, left ventricular systolic dyssynchrony (LVSD) with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion could referred to as subclinical myocardial damage, which is difficult to diagnose at an early stage. Epicardial adipose tissue, a distinctive heart-specific visceral fat, is closely related to various cardiovascular diseases. The objective of this study was to investigate the correlation between epicardial fat volume (EFV) and subclinical myocardial damage in T2DM patients. Methods: This retrospective cross-sectional study included 117 T2DM patients with normal myocardial perfusion by single photon emission computed tomography-computed tomography (SPECT-CT) and normal LVEF by echocardiography. The study was conducted from January 2018 to December 2022. Patient data were collected through electronic medical records including basic patient information, medical history, laboratory tests, and medication data. The EFV was quantified through a non-contrast CT scan. Quantitative indicators of LVSD including phase standard deviation (PSD) and phase histogram bandwidth (PBW) were obtained through phase analysis of the gated rest myocardial perfusion imaging (MPI). Additionally, 83 healthy individuals at the same time were selected to gain the reference threshold of LVSD indicators (13.1° for PSD and 37.6° for PBW). Univariate and multivariable logistic regression models were performed to analyze factors influencing LVSD. A generalized additive model (GAM) was applied to explore the relationship between EFV and LVSD. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of EFV for LVSD. Results: Among all patients, 32 (27.4%) patients had LVSD. Compared with the non-LVSD group, the body mass index (BMI) and EFV were higher in the LVSD group (25.83±2.66 vs. 23.94±3.13 kg/m2; 142.41±44.17 vs. 108.01±38.24 cm3, respectively, both P<0.05). Multivariate regression analysis revealed that EFV was independently associated with LVSD [odds ratio (OR) =1.19; 95% confidence interval (CI): 1.06-1.34; P=0.003]. Age, BMI, incidence of hypertension, and LVSD were increased with tertiles of EFV (all P<0.05). The GAM indicated a linear association between EFV and LVSD. The ROC curve analysis concluded that the area under the curve (AUC) of EFV for predicting subclinical myocardial damage in T2DM patients was 0.732 (95% CI: 0.633-0.831, P<0.001), with the optimal threshold of 122.26 cm3, sensitivity of 71.9%, and specificity of 69.4%. Conclusions: EFV is an independent risk factor for LVSD in T2DM patients with normal LVEF and normal MPI, which could potentially serve as a novel imaging marker and a potential therapeutic target for subclinical myocardial damage.

An unexpected interaction between diabetes and cardiovascular diseases on cognitive function: A cross-sectional study.

OBJECTIVE: Impaired cognitive function in older individuals significantly affects quality of life. The interaction between comorbid diabetes and cardiovascular disease (CVD) and its impact on cognitive impairment remains unclear. METHODS: This study analyzed 2564 subjects from the National Health and Nutrition Examination Survey dataset. Cognitive function was measured using various scores, including CERAD Total Score, CERAD Delayed Recall Score (CDRS), Animal Fluency Total Score, and Digit Symbol Score. Multiple regression models were constructed to explore the relationship between different diseases and cognitive function, considering covariates such as age, sex, education, body mass index, alcohol intake, smoking, physical activity, kidney function, and hypertension. RESULTS: After adjusting for multiple factors, the presence of CVD, diabetes, or both showed a significant negative association with the total cognitive score. The CDRS was associated with both CVD and diabetes. The Digit Symbol score was associated with the presence of CVD, diabetes, or both. No significant differences were found between patients with diabetes and CVD in cognitive test results. An interaction between CVD and diabetes was observed in relation to the CDRS but not in other test scores or the total score. CONCLUSION: The individual impact of each disease on cognitive function was not significant. However, an interaction between CVD and diabetes was found when both diseases coexisted, specifically in relation to delayed learning ability.

Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.

BACKGROUND: To introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC). METHODS: Retrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models. A dual-stream model fusing PET and CT and a three-stream transfer learning model (TS_TL) integrating clinical data were also developed. Image preprocessing includes semi-automatic segmentation, resampling, and image cropping. Considering the impact of class imbalance, the performance of the model was evaluated using ROC curves and AUC values. RESULTS: TS_TL model demonstrated promising performance in predicting the EGFR mutation status, with an AUC of 0.883 (95%CI = 0.849-0.917) in the training set and 0.730 (95%CI = 0.629-0.830) in the independent test set. Particularly in advanced LADC, the model achieved an AUC of 0.871 (95%CI = 0.823-0.919) in the training set and 0.760 (95%CI = 0.638-0.881) in the test set. The model identified distinct activation areas in solid or subsolid lesions associated with wild and mutant types. Additionally, the patterns captured by the model were significantly altered by effective tyrosine kinase inhibitors treatment, leading to notable changes in predicted mutation probabilities. CONCLUSION: PET/CT deep learning model can act as a tool for predicting EGFR mutation in LADC. Additionally, it offers clinicians insights for treatment decisions through evaluations both before and after treatment.

Sex Differences in Coronary Inflammation and Atherosclerosis Phenotypes in Response to Imaging Marker of Stress-Related Neural Activity.

BACKGROUND: Sex-specific differences in coronary phenotypes in response to stress have not been elucidated. This study investigated the sex-specific differences in the coronary computed tomography angiography-assessed coronary response to mental stress. METHODS: This retrospective study included patients with coronary artery disease and without cancer who underwent resting 18F-fluorodexoyglucose positron emission tomography/computed tomography and coronary computed tomography angiography within 3 months. 18F-flourodeoxyglucose resting amygdalar uptake, an imaging biomarker of stress-related neural activity, coronary inflammation (fat attenuation index), and high-risk plaque characteristics were assessed by coronary computed tomography angiography. Their correlation and prognostic values were assessed according to sex. RESULTS: A total of 364 participants (27.7% women and 72.3% men) were enrolled. Among those with heightened stress-related neural activity, women were more likely to have a higher fat attenuation index (43.0% versus 24.0%; P=0.004), while men had a higher frequency of high-risk plaques (53.7% versus 39.3%; P=0.036). High amygdalar 18F-flourodeoxyglucose uptake (B-coefficient [SE], 3.62 [0.21]; P<0.001) was selected as the strongest predictor of fat attenuation index in a fully adjusted linear regression model in women, and the first-order interaction term consisting of sex and stress-related neural activity was significant (P<0.001). Those with enhanced imaging biomarkers of stress-related neural activity showed increased risk of major adverse cardiovascular event both in women (24.5% versus 5.1%; adjusted hazard ratio, 3.62 [95% CI, 1.14-17.14]; P=0.039) and men (17.2% versus 6.9%; adjusted hazard ratio, 2.72 [95% CI, 1.10-6.69]; P=0.030). CONCLUSIONS: Imaging-assessed stress-related neural activity carried prognostic values irrespective of sex; however, a sex-specific mechanism linking psychological stress to coronary plaque phenotypes existed in the current hypothesis-generating study. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05545618.

The combination of maximum standardized uptake value and clinical parameters for improving the accuracy in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.

Background: Anterior mediastinal masses are relatively uncommon, and mediastinal lymphomas are the malignancies most likely to be confused with thymic epithelial tumors (TETs). The aim of this study was to investigate whether the combination of 18fluorine-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) findings and clinical parameters is useful in differentiating lymphoma from TETs in anterior mediastinal masses. Methods: This retrospective study consecutively included 304 patients with anterior mediastinal masses (244 TETs and 60 lymphomas) who underwent 18F-FDG PET-CT 1 to 2 weeks before tumor resection or biopsy between August 2016 and March 2022. The correlations between the maximum standardized uptake value (SUVmax) of tumors and clinical parameters of patients with histology subtypes were analyzed. Receiver operating characteristic curve analysis was used to obtain the optimal cutoff values of age, lactate dehydrogenase (LDH), tumor size, and SUVmax to predict lymphoma. Logistic regression analysis was used to identify potential predictive factors for lymphoma. Results: Lymphoma was significantly associated with younger patient age, higher LDH level, larger tumor size, and higher SUVmax compared to TETs (P<0.001). In the modeling cohort, age ≤40.5 years, LDH level ≥197 U/L, tumor size ≥10.72 cm, and SUVmax ≥11.95 were identified as independent predictors for lymphoma with odds ratios of 20.14 [95% confidence interval (CI): 6.02-67.40; P<0.001], 4.89 (95% CI: 1.27-18.89; P=0.021), 8.82 (95% CI: 2.31-33.69; P=0.001), and 30.01 (95% CI: 6.59-136.72; P<0.001), respectively. The accuracy of age, LDH, tumor size, and SUVmax in predicting lymphoma was 84.8%, 67.8%, 85.2%, and 78.3% respectively. The combination of the four above parameters could improve the predictive accuracy to 89.1%, and in the validation cohort, this combination increased the predictive accuracy to 87.8%. Conclusions: SUVmax on 18F-FDG PET-CT has the potential ability to discriminate lymphomas from TETs in the diagnosis of anterior mediastinal masses, and the combination of SUVmax with clinical parameters can improve the diagnostic accuracy. This combination may therefore may be helpful in avoiding unnecessary operation in patients with anterior mediastinal lymphomas.

The relationship between right atrial wall inflammation and poor prognosis of atrial fibrillation based on 18F-FDG positron emission tomography/computed tomography.

Background: Atrial fibrillation (AF) has been identified to increase stroke risk, even after oral anticoagulants (OACs), and the recurrence rate is high after radiofrequency catheter ablation (RFCA). Inflammation is an essential factor in the occurrence and persistence of AF. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) is an established molecular imaging modality to detect local inflammation. We aimed to investigate the relationship between atrial inflammatory activity and poor prognosis of AF based on 18F-FDG PET/CT. Methods: A total of 204 AF patients including 75 with paroxysmal AF (ParAF) and 129 with persistent AF (PerAF) who underwent PET/CT before treatment were enrolled in this prospective cohort study. Clinical data, electrocardiograph (ECG), echocardiography, and cardiac 18F-FDG uptake were collected. Follow-up information was obtained from patient clinical case notes or telephone reviews, with the starting point being the time of PET/CT scan. The follow-up deadline was either the date of AF recurrence after RFCA, new-onset stroke, or May 2023. Cox proportional hazards regression models were used to identify predictors of poor prognosis and hazard ratios (HRs) with 95% confidence intervals (CIs) was calculated. Results: Median follow-up time was 29 months [interquartile range (IQR), 22-36 months]. Poor prognosis occurred in 52 patients (25.5%), including 34 new-onset stroke patients and 18 recrudescence after RFCA. The poor prognosis group had higher congestive heart failure, hypertension, age ≥75 years (doubled), diabetes mellitus, prior stroke or transient ischemic attack (TIA) or thromboembolism (doubled), vascular disease, age 65-74 years, sex category (female) (CHA2DS2-VASc) score [3.0 (IQR, 1.0-3.75) vs. 2.0 (IQR, 1.0-3.0), P=0.01], right atrial (RA) wall maximum standardized uptake value (SUVmax) (4.13±1.82 vs. 3.74±1.58, P=0.04), higher percentage of PerAF [39 (75.0%) vs. 90 (59.2%), P=0.04], left atrial (LA) enlargement [45 (86.5%) vs. 104 (68.4%), P=0.01], and RA wall positive FDG uptake [40 (76.9%) vs. 79 (52.0%), P=0.002] compared with the non-poor prognosis group. Univariate and multivariate Cox proportional hazard regression analysis concluded that only CHA2DS2-VASc score (HR, 1.29; 95% CI: 1.06-1.57; P=0.01) and RA wall positive FDG uptake (HR, 2.68; 95% CI: 1.10-6.50; P=0.03) were significantly associated with poor prognosis. Conclusions: RA wall FDG positive uptake based on PET/CT is tightly related to AF recurrence after RFCA or new-onset stroke after antiarrhythmic and anticoagulation treatment.

An Electrochemically Initiated Self-Limiting Hydrogel Electrolyte for Dendrite-Free Zinc Anode.

The zinc dendrite growth generally relies upon a "positive-feedback" mode, where the fast-grown tips receive higher current densities and ion fluxes. In this study, a self-limiting polyacrylamide (PAM) hydrogel that presents negative feedback to dendrite growth is developed. The monomers are purposefully polymerized at the dendrite tips, then the hydrogel reduces the local current density and ion flux by limiting zinc ion diffusion with abundant functional groups. As a consequence, the accumulation at the dendrite tips is restricted, and the (002) facets-oriented deposition is achieved. Moreover, the refined porous structure of the gel enhances Coulombic Efficiency by reducing water activity. Due to the synergistic effects, the zinc anodes perform an ultralong lifetime of 5100 h at 0.5 mA cm-2 and 1500 h at 5 mA cm-2, which are among the best records for PAM-based gel electrolytes. Further, the hydrogel significantly prolongs the lifespan of zinc-ion batteries and capacitors by dozens of times. The developed in situ hydrogel presents a feasible and cost-effective way to commercialize zinc anodes and provides inspiration for future research on dendrite suppression using the negative-feedback mechanism.

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review.

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive. 18F-FDG PET/CT can be used as a noninvasive molecular imaging approach, and radiomics can acquire high-throughput data from standard images. These methods play an increasingly prominent role in diagnosing and treating cancers. Herein, we reviewed the progress in applying 18F-FDG PET/CT and radiomics in lung adenocarcinoma clinical research and how these data are analyzed via traditional statistics, machine learning, and deep learning to predict EGFR mutation status, all of which achieved satisfactory results. Traditional statistics extract features effectively, machine learning achieves higher accuracy with complex algorithms, and deep learning obtains significant results through end-to-end methods. Future research should combine these methods to achieve more accurate predictions, providing reliable evidence for the precision treatment of lung adenocarcinoma. At the same time, facing challenges such as data insufficiency and high algorithm complexity, future researchers must continuously explore and optimize to better apply to clinical practice.

Right atrial wall inflammation detected by 18F-FDG PET/CT may be significantly associated with persistent atrial fibrillation: a prospective case-control study.

AIM: Atrial fibrillation (AF) is a progressive disease from paroxysmal to persistent, and persistent AF (PerAF) had worse prognosis. AF has potential link with inflammation, but it is not clear whether PerAF or paroxysmal AF (ParAF) is more closely related to inflammation. On the basis of inhibiting myocardial physiological uptake, 18F-fluorodeoxyglucosepositron emission tomography/computed tomography (18F-FDG PET/CT) is an established imaging modality to detect cardiac inflammation. We aimed to decipher the association between AF and atrial inflammatory activity by 18F-FDG PET/CT. METHODS: Thirty-five PerAF patients were compared to age and sex matched ParAF group with baseline 18F-FDG PET/CT scans prior to radiofrequency catheter ablation (RFCA) in the prospective case-control study. High-fat and low-carbohydrate diet and prolonged fast (HFLC+Fast) was applied to all AF patients before PET/CT. Then 22 AF patients with positive right atrial (RA) wall FDG uptake (HFLC+Fast) were randomly selected and underwent HFLC+Fast+heparin the next day. The CHA2DS2-VASc score was calculated to evaluate the risk of stroke. Clinical data, ECG, echocardiography, and atrial 18F-FDG uptake were compared. RESULTS: PerAF patients had significantly higher probability of RA wall positive FDG uptake and higher SUVmax than ParAF group [91.4% VS. 28.6%, P < 0.001; SUVmax: 4.10(3.20-4.90) VS. 2.60(2.40-3.10), P < 0.001]. Multivariate logistic regression analyses demonstrated that RA wall SUVmax was the independent influencing factor of PerAF (OR = 1.80, 95%CI 1.02-3.18, P = 0.04). In 22 AF patients with RA wall positive FDG uptake (HFLC+Fast), the "HFLC+Fast+Heparin" method did not significantly change RA wall FDG uptake evaluated by either quantitative analysis or visual analysis. High CHA2DS2-VASc score group had higher RA wall 18F-FDG uptake [3.35 (2.70, 4.50) vs, 2.8 (2.4, 3.1) P = 0.01]. CONCLUSIONS: RA wall FDG positive uptake was present mainly in PerAF. A higher RA wall 18F-FDG uptake was an independent influencing factor of PerAF. RA wall FDG uptake based on 18F-FDG PET/CT may indicate pathological inflammation. TRIAL REGISTRATION: http://www.chictr.org.cn , ChiCTR2000038288.

Dissemination feature based on PET/CT is a risk factor for diffuse large B cell lymphoma patients outcome.

BACKGROUND: 18F-FDG PET/CT provides precise information about dissemination of lymphoma lesions. Dmax, defined as distance between the two lesions that were farthest apart by PET/CT, was found to be a promising predictor of Diffuse large B-cell lymphoma (DLBCL) outcome in a small size of clinical trial data. We analyzed the impact of Dmax on the outcome of a large real-world DLBCL cohort. METHODS: Data of newly diagnosed DLBCL at the Third Affiliated Hospital of Soochow University were retrospectively collected. Baseline Dmax, clinical data and survival information were recorded. A metabolic parameter, metabolic bulk volume (MBV), was also measured to verify the independent impact of Dmax. RESULTS: Optimal cut-off values for Dmax and MBV were 45.34 cm and 21.65 cm3. With a median follow-up of 32 months, Dmax significantly impacted progression-free survival (PFS) and overall survival (OS) in 253 DLBCL patients. For Dmaxlow and Dmaxhigh groups, estimated 3-year OS were 87.0% and 53.8% (p < 0.001), while 3-year PFS were 77.3% and 37.3% (p < 0.001). And for MBVlow and MBVhighgroups, 3-year OS were 84.5% and 58.8% (p < 0.001), and 3-year PFS were 68.7% and 50.4% (p = 0.003). Multivariate analysis identified Dmax and Eastern Cooperative Oncology Group performance status (ECOG PS) independently associated with PFS and OS, while MBV only independently associated with OS. A Dmax revised prognostic index (DRPI) combining Dmax and ECOG PS identified an ultra-risk DLBCL population with 3-year PFS of 31.7% and 3-year OS of 38.5%. The area under the curve (AUC) showed that this model performed better than International prognostic Index (IPI). CONCLUSION: Dmax is a new and promising indicator to investigate dissemination of lymphoma lesions associated with the outcome of DLBCL. It significantly contributes to stratification of patients with disparate outcomes. TRIAL REGISTRATION: This research has been retrospectively registered in the Ethics Committee institutional of the Third Affiliated Hospital of Soochow University, and the registration number was approval No. 155 (approved date: 31 May 2022).

Epicardial fat volume, an independent risk factor for major adverse cardiovascular events, had an incremental prognostic value to myocardial perfusion imaging in Chinese populations with suspected or known coronary artery disease with a normal left ventricular ejection fraction.

Background: Most coronary artery disease (CAD) patients with a normal left ventricular ejection fraction (LVEF) experience a poor prognosis. Single-photon emission computerized tomography (SPECT)-myocardial perfusion imaging (MPI), a routine examination, is useful in assessing risk and predicting major adverse cardiovascular events (MACEs) in populations with suspected or known CAD. SPECT/CT is a "one-stop shop" examination, which, through non-contrast CT, can produce attenuation correction for MPI and obtain information on coronary artery calcium (CAC) and epicardial fat volume (EFV) simultaneously. This study aims to investigate the predictive and incremental value of EFV to MPI for MACE in Chinese populations with suspected or known CAD with a normal LVEF. Methods and results: We retrospectively studied 290 suspected or known CAD inpatients with a normal LVEF who underwent SPECT/CT between February 2014 and December 2017. Abnormal MPI was defined as a summed stress score ≥4 or summed difference score ≥2. EFV and CAC were calculated using non-contrast CT. The end date of follow-ups was in February 2022. The follow-up information was obtained from the clinical case notes of the patients or reviews of telephone calls. MACE was defined as cardiac death, late coronary revascularization ≥3 months after MPI, non-fatal myocardial infarction, angina-related rehospitalization, heart failure, and stroke. During the 76-month follow-up, the event rate was 32.0% (93/290). Univariate and multivariate Cox regression analyses concluded that high EFV (>108.3 cm3) [hazard ratio (HR): 3.3, 95% CI: 2.1-5.2, P < 0.000] and abnormal MPI (HR: 1.8, 95% CI: 1.1-2.8, P = 0.010) were independent risk factors for MACE. The event-free survival of patients with high EFV was significantly lower than that of the low EFV group (log-rank test P < 0.001). In the subgroup with normal MPI, high EFV was associated with reduced event-free survival (log-rank P < 0.01), with a higher annualized event rate (8.3% vs. 1.9%). Adding high EFV to MPI could predict MACEs more effectively, with a higher concordance index (0.56-0.69, P < 0.01), higher global chi square (7.2-41.4, P < 0.01), positive integrated discrimination improvement (0.10, P < 0.01), and net reclassification index (0.37, P < 0.01). Conclusions: In Chinese populations with suspected or known CAD with normal LVEF, high EFV was an independent risk factor for MACE after adjusting for traditional risk factors, CAC and MPI. In subgroups with normal MPI, EFV could also improve risk stratification. Adding EFV to MPI had an incremental value for predicting MACE.

Gold Nanoparticles Enhance the Ability of Radiotherapy to Induce Immunogenic Cell Death in Glioblastoma.

Background: Radiation therapy (RT) is commonly used to treat glioblastoma, but its immunomodulatory effect on tumors, through mechanisms such as immunogenic cell death (ICD), is relatively weak. Gold nanoparticles (AuNPs) have been suggested as potential radio-sensitizers, but it is unclear if they can enhance radiation-induced ICD. This study aimed to investigate the potential of AuNPs to improve the effectiveness of radiation-induced ICD. Methods: G422 cells were treated with a combination of AuNPs and RT to induce cell death. Various assays were conducted to assess cell death, surface expression of CRT, and release of HMGB1 and ATP. In vitro co-culture experiments with bone marrow-derived dendritic cells (BMDCs) were performed to analyze the immunogenicity of dying cancer cells. Flow cytometry was used to measure the maturation rate of BMDCs. An in vivo mouse tumor prophylactic vaccination model was employed to assess immunogenicity. Results: The study findings presented here confirm that the combination of radiotherapy (RT) with AuNPs can induce a stronger ICD effect on glioblastoma cells compared to using RT alone. Specifically, treatment with AuNPs combined with RT resulted in the emission of crucial damage-associated molecular patterns (DAMPs) such as CRT, HMGB1 (479.41±165.34pg/mL vs 216.04±178.16 pg/mL, *P<0.05) and ATP (The release of ATP in the AuNPs + RT group was 1.2 times higher than in the RT group, *P<0.05). The proportion of BMDC maturation rate was higher in the group treated with AuNPs and RT compared to the group treated with RT alone. (32.53±0.52% vs 25.03±0.28%,***P < 0.001). In the tumor vaccine experiment, dying tumor cells treated with AuNPs and RT effectively inhibited tumor growth in mice when exposed to living tumor cells. Conclusion: These results indicate that AuNPs have the ability to enhance RT-induced ICD.

Predictive value of SUVmax in visceral pleural invasive lung adenocarcinoma with different diameters.

OBJECTIVES: This study aimed to investigate predictive visceral pleural invasion (VPI) occurrence value of the maximum standardized uptake value (SUVmax) in patients with lung adenocarcinoma (LA). PATIENTS AND METHODS: A total of 388 LA patients were divided into D1ab, D1c, D1, D2, D2a, D2b, D3, and all patient groups based on their tumor diameter (D). Patients were also classified into negative VPI (VPI-n) and positive VPI (VPI-p) groups according to VPI presence. SUVmax of patients was measured with 18F-fluorodeoxyglucose (FDG) by PET/computed tomography (18F-PET/CT). Receiver operating characteristic (ROC) analysis and the area under curve (AUC) of SUVmax were applied to determine optimal cut-off value for predicting VPI occurrence. RESULTS: There were significant differences in SUVmax between VPI-n and VPI-p groups ( P  < 0.05) at the same tumor diameter. SUVmax cut-off value and sensitivity (Se,%) of VPI occurrence in each group were following: D1ab was 3.79 [AUC = 0.764, P  < 0.001], Se86.11%; D1c was 5.47 (AUC = 0.706, P  < 0.001), Se 93.75%; D1 was 5.49 (AUC = 0.731, P  < 0.001), Se 79.76%; D2 was 7.36 (AUC = 0.726, P  < 0.001), Se81.67%. All patient group was 7.26 (AUC = 0.735, P  < 0.001), Se74.19%. CONCLUSION: In LA patients with the same diameter, SUVmax of the VPI-p group was significantly higher than that of the VPI-n group. The cut-off value of SUVmax for predicting VPI of T1 stage, T1 substages, and T2 stage LA could be determined through ROC curve. SUVmax measurement by PET/CT scan in stratified tumor size is helpful for predicting VPI occurrences of the physician.

Exploring the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer patients.

PURPOSE: Our study intended to explore the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer (NSCLC) patients detected by next-generation sequencing (NGS). METHODS: NGS assay was performed in 1737 NSCLC patients, a total of 88 HER2 alterations and 176 negative HER2 with EGFR-negative patients were randomly selected for this study. RESULTS: When the HER2 status with EGFR-negative group was analyzed, multivariate analysis showed that smoking status, primary tumor SUVmax (pSUVmax) < 13.03 and stage were the independent deterministic factors of HER2 alterations. Multivariate cox regression analysis revealed that HER2 status, age, smoking status and stage were independent risk factors for overall survival (OS) in EGFR-negative NSCLC patients with different HER2 status. When the HER2 alterations group was separately analyzed, multivariate analysis demonstrated that low pSUVmax < 15.32 and histology were the independent deterministic factors of HER2 mutation. Multivariate cox regression analysis revealed that pSUVmax, smoking status, nodal involvement and treatment methods were independent risk factors for OS in EGFR-negative NSCLC patients with HER2 alterations. CONCLUSION: The study revealed that low pSUVmax was associated with HER2 alterations in EGFR-negative NSCLC patients, moreover HER2 mutation and HER2 amplification exhibited distinct 18F-FDG metabolic and clinical characteristics. Furthermore, it explored the prognostic value of HER2 alterations and 18F-FDG PET/CT metabolic parameters of pSUVmax in EGFR-negative NSCLC patients.

Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume.

We sought to establish an explainable machine learning (ML) model to screen for hemodynamically significant coronary artery disease (CAD) based on traditional risk factors, coronary artery calcium (CAC) and epicardial fat volume (EFV) measured from non-contrast CT scans. 184 symptomatic inpatients who underwent Single Photon Emission Computed Tomography/Myocardial Perfusion Imaging (SPECT/MPI) and Invasive Coronary Angiography (ICA) were enrolled. Clinical and imaging features (CAC and EFV) were collected. Hemodynamically significant CAD was defined when coronary stenosis severity ≥ 50% with a matched reversible perfusion defect in SPECT/MPI. Data was randomly split into a training cohort (70%) on which five-fold cross-validation was done and a test cohort (30%). The normalized training phase was preceded by the selection of features using recursive feature elimination (RFE). Three ML classifiers (LR, SVM, and XGBoost) were used to construct and choose the best predictive model for hemodynamically significant CAD. An explainable approach based on ML and the SHapley Additive exPlanations (SHAP) method was deployed to generate individual explanation of the model's decision. In the training cohort, hemodynamically significant CAD patients had significantly higher age, BMI and EFV, higher proportions of hypertension and CAC comparing with controls (P all < .05). In the test cohorts, hemodynamically significant CAD had significantly higher EFV and higher proportion of CAC. EFV, CAC, diabetes mellitus (DM), hypertension, and hyperlipidemia were the highest ranking features by RFE. XGBoost produced better performance (AUC of 0.88) compared with traditional LR model (AUC of 0.82) and SVM (AUC of 0.82) in the training cohort. Decision Curve Analysis (DCA) demonstrated that XGBoost model had the highest Net Benefit index. Validation of the model also yielded a favorable discriminatory ability with the AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 0.89, 68.0%, 96.8%, 94.4%, 79.0% and 83.9% in the XGBoost model. A XGBoost model based on EFV, CAC, hypertension, DM and hyperlipidemia to assess hemodynamically significant CAD was constructed and validated, which showed favorable predictive value. ML combined with SHAP can offer a transparent explanation of personalized risk prediction, enabling physicians to gain an intuitive understanding of the impact of key features in the model.

18F-FDG PET-CT for the prediction of mortality in patients with dermatomyositis and without malignant tumors: a pilot study.

Background: 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) is typically used to screen malignancy in patients with dermatomyositis (DM). The aim of this study was to investigate the value of using PET-CT in assessing the prognosis of patients with DM and without malignant tumors. Methods: A total of 62 patients with DM who underwent 18F-FDG PET-CT were enrolled in the retrospective cohort study. Clinical data and laboratory indicators were obtained. The muscle max standardized uptake value (SUVmax), splenic SUVmax, target-to-background ratio (TBR) of the aorta, pulmonary highest value (hv)/SUVmax, epicardial fat volume (EFV), and coronary artery calcium (CAC) were measured using 18F-FDG PET-CT. The follow-up was conducted until March 2021, and the endpoint was death from any cause. Univariable and multivariable Cox regression analyses were used to analyze prognostic factors. The survival curves were produced with the Kaplan-Meier method. Results: The median duration of follow-up was 36 [interquartile range (IQR), 14-53] months. The survival rates were 85.2% and 73.4% for 1 and 5 years, respectively. A total of 13 (21.0%) patients died during a median follow-up of 7 (IQR, 4-15.5) months. Compared with the survival group, the death group had significantly higher levels of C-reactive protein [CRP; median (IQR), 4.2 (3.0, 6.0) vs. 6.30 (3.7, 22.8)], hypertension [7 (14.3%) vs. 6 (46.2%)], interstitial lung disease [ILD; 26 (53.1%) vs. 12 (92.3%)], positive anti-Ro52 antibody [19 (38.8%) vs. 10 (76.9%)], pulmonary FDG uptake [median (IQR), 1.8 (1.5, 2.9) vs. 3.5 (2.0, 5.8)], CAC [1 (2.0%) vs. 4 (30.8%)], and EFV [median (IQR), 74.1 (44.8, 92.1) vs. 106.5 (75.0, 128.5)] (all P values <0.001). Univariable and multivariable Cox analyses identified high pulmonary FDG uptake [hazard ratio (HR), 7.59; 95% confidence interval (CI), 2.08-27.76; P=0.002] and high EFV (HR, 5.86; 95% CI, 1.77-19.42; P=0.004) as independent risk factors for mortality. The survival rate was significantly lower in patients with the concurrent presence of high pulmonary FDG uptake and high EFV. Conclusions: Pulmonary FDG uptake and EFV detected with PET-CT were independent risk factors for death in patients with DM and without malignant tumors. Patients with the concurrent presence of high pulmonary FDG uptake and high EFV had a worse prognosis compared with patients with 1 or neither of these two risk factors. Early treatment should be applied in patients with concurrent presence of high pulmonary FDG uptake and high EFV to improve the survival rate.

Stress-Related Neural Activity Associates With Coronary Plaque Vulnerability and Subsequent Cardiovascular Events.

BACKGROUND: Stress-related neural activity (SNA) assessed by amygdalar activity can predict cardiovascular events. However, its mechanistic linkage with plaque vulnerability is not fully elucidated. OBJECTIVES: The authors aimed to investigate the association of SNA with coronary plaque morphologic and inflammatory features as well as their ability in predicting major adverse cardiovascular events (MACE). METHODS: A total of 299 patients with coronary artery disease (CAD) and without cancer underwent 18F-fluorodexoyglucose positron emission tomography/computed tomography (PET/CT) and available coronary computed tomographic angiography (CCTA) between January 1, 2013, and December 31, 2020. SNA and bone-marrow activity (BMA) were assessed with validated methods. Coronary inflammation (fat attenuation index [FAI]) and high-risk plaque (HRP) characteristics were assessed by CCTA. Relations between these features were analyzed. Relations between SNA and MACE were assessed with Cox models, log-rank tests, and mediation (path) analyses. RESULTS: SNA was significant correlated with BMA (r = 0.39; P < 0.001) and FAI (r = 0.49; P < 0.001). Patients with heightened SNA are more likely to have HRP (40.7% vs 23.5%; P = 0.002) and increase risk of MACE (17.2% vs 5.1%, adjusted HR 3.22; 95% CI: 1.31-7.93; P = 0.011). Mediation analysis suggested that higher SNA associates with MACE via a serial mechanism involving BMA, FAI, and HRP. CONCLUSIONS: SNA is significantly correlated with FAI and HRP in patients with CAD. Furthermore, such neural activity was associated with MACE, which was mediated in part by leukopoietic activity in the bone marrow, coronary inflammation, and plaque vulnerability.

Association of epicardial adipose tissue volume with increased risk of hemodynamically significant coronary artery disease.

Background: Epicardial adipose tissue (EAT) is closely related to coronary artery disease (CAD). Hemodynamically significant CAD has a worse prognosis and is more likely to benefit from revascularization. However, the specific relationship between EAT and hemodynamically significant CAD remains unclear. Methods: A total of 164 inpatients received single-photon emission computerized tomography-myocardial perfusion imaging (SPECT/MPI) and coronary angiography (CAG) between March 2018 and October 2019 at the Third Affiliated Hospital of Soochow University were enrolled in the retrospective cross-sectional study. Data on body mass index (BMI), hypertension, hyperlipidemia, diabetes mellitus (DM), active smoking, and symptoms were gathered. Epicardial fat volume (EFV) and coronary artery calcium (CAC) were quantified by noncontrast computed tomography (CT). Hemodynamically significant CAD was defined by coronary stenosis severity ≥50% with reversible perfusion defects in the corresponding areas of SPECT/MPI. Results: A total of 37.8% of patients had hemodynamically significant CAD. Age and BMI increased with tertiles of EFV (P for trend =0.009 and P<0.001). The ratios of hemodynamically significant CAD in EFV from low to high were 16.4%, 37.0%, and 60.0%, respectively (P for the trend <0.001). In univariate regression analysis, EFV was associated with hemodynamically significant CAD [odds ratio (OR) per 10 cm3 =1.36; 95% confidence interval (CI): 1.20-1.55; P<0.001]. After correcting for traditional risk factors and CAC, EFV was firmly linked to hemodynamically significant CAD (OR per 10 cm3 =1.53; 95% CI: 1.25-1.88; P<0.001). With an increasing trend in EFV for the tripartite groups, the likelihood of hemodynamically significant CAD increased significantly (P for trend <0.001). There was a saturation effect between EFV and hemodynamically significant CAD according to the generalized additive model (GAM). When EFV <134.43 cm3, EFV was linearly correlated with hemodynamically significant CAD (OR per 10 cm3 =2.06; 95% CI: 1.45-2.94; P<0.001). When EFV ≥134.43 cm3, the hemodynamically significant CAD risk was steeper and gradually reached saturation. Hypertension affected the relationship between EFV and hemodynamically significant CAD (P for the interaction =0.02) with an interaction effect. Conclusions: There was a robust relationship between EFV and hemodynamically significant CAD. After adjustment for confounders, we found that the risk of hemodynamically significant CAD onset increased nonlinearly for EFV above 134.4 cm3. This refined understanding of the relationship is helpful for the accurate clinical prediction of hemodynamically significant CAD.