Joint Exposure to Ambient Air Pollutants, Genetic Risk, and Ischemic Stroke: A Prospective Analysis in UK Biobank.

BACKGROUND: Our primary objective was to assess the association between joint exposure to various air pollutants and the risk of ischemic stroke (IS) and the modification of the genetic susceptibility. METHODS: This observational cohort study included 307 304 British participants from the United Kingdom Biobank, who were stroke-free and possessed comprehensive baseline data on genetics, air pollutant exposure, alcohol consumption, and dietary habits. All participants were initially enrolled between 2006 and 2010 and were followed up until 2022. An air pollution score was calculated to assess joint exposure to 5 ambient air pollutants, namely particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, as well as nitrogen oxide and nitrogen dioxide. To evaluate individual genetic risk, a polygenic risk score for IS was calculated for each participant. We adjusted for demographic, social, economic, and health covariates. Cox regression models were utilized to estimate the associations between air pollution exposure, polygenic risk score, and the incidence of IS. RESULTS: Over a median follow-up duration of 13.67 years, a total of 2476 initial IS events were detected. The hazard ratios (95% CI) of IS for per 10 µg/m3 increase in particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, nitrogen dioxide, and nitrogen oxide were 1.73 (1.33-2.14), 1.24 (0.88-1.70), 1.13 (0.89-1.33), 1.03 (0.98-1.08), and 1.04 (1.02-1.07), respectively. Furthermore, individuals in the highest quintile of the air pollution score exhibited a 29% to 66% higher risk of IS compared with those in the lowest quintile. Notably, participants with both high polygenic risk score and air pollution score had a 131% (95% CI, 85%-189%) greater risk of IS than participants with low polygenic risk score and air pollution score. CONCLUSIONS: Our findings suggested that prolonged joint exposure to air pollutants may contribute to an increased risk of IS, particularly among individuals with elevated genetic susceptibility to IS.

Laser capture microdissection transcriptome (LCM RNA-seq) reveals BcDFR is a key gene in anthocyanin synthesis of non-heading Chinese cabbage.

BACKGROUND: Purple non-heading Chinese cabbage [Brassica campestris (syn. Brassica rapa) ssp. chinensis] has become popular because of its richness in anthocyanin. However, anthocyanin only accumulates in the upper epidermis of leaves. Further studies are needed to investigate the molecular mechanisms underlying the specific accumulation of it. RESULTS: In this study, we used the laser capture frozen section method (LCM) to divide purple (ZBC) and green (LBC) non-heading Chinese cabbage leaves into upper and lower epidermis parts (Pup represents the purple upper epidermis, Plow represents the purple lower epidermis, Gup represents the green upper epidermis, Glow represents the green lower epidermis). Through transcriptome sequencing, we found that the DIHYDROFLAVONOL 4-REDUCTASE-encoding gene BcDFR, is strongly expressed in Pup but hardly in others (Plow, Gup, Glow). Further, a deletion and insertion in the promoter of BcDFR in LBC were found, which may interfere with BcDFR expression. Subsequent analysis of gene structure and conserved structural domains showed that BcDFR is highly conserved in Brassica species. The predicted protein-protein interaction network of BcDFR suggests that it interacts with almost all functional proteins in the anthocyanin biosynthesis pathway. Finally, the results of the tobacco transient expression also demonstrated that BcDFR promotes the synthesis and accumulation of anthocyanin. CONCLUSIONS: BcDFR is specifically highly expressed on the upper epidermis of purple non-heading Chinese cabbage leaves and regulates anthocyanin biosynthesis and accumulation. Our study provides new insights into the functional analysis and transcriptional regulatory network of anthocyanin-related genes in purple non-heading Chinese cabbage.

Dynamic evolution of COVID-19 vaccine hesitancy over 2021-2023 among Chinese population: Repeated nationwide cross-sectional study.

Globally, the rollout of COVID-19 vaccine had been faced with a significant barrier in the form of vaccine hesitancy. This study adopts a multi-stage perspective to explore the prevalence and determinants of COVID-19 vaccine hesitancy, focusing on their dynamic evolutionary features. Guided by the integrated framework of the 3Cs model (complacency, confidence, and convenience) and the EAH model (environmental, agent, and host), this study conducted three repeated national cross-sectional surveys. These surveys carried out from July 2021 to February 2023 across mainland China, targeted individuals aged 18 and older. They were strategically timed to coincide with three critical vaccination phases: universal coverage (stage 1), partial coverage (stage 2), and key population coverage (stage 3). From 2021 to 2023, the surveys examined sample sizes of 29 925, 6659, and 5407, respectively. The COVID-19 vaccine hesitation rates increased from 8.39% in 2021 to 29.72% in 2023. Urban residency, chronic condition, and low trust in vaccine developer contributed to significant COVID-19 vaccine hesitancy across the pandemic. Negative correlations between the intensity of vaccination policies and vaccine hesitancy, and positive correlations between vaccine hesitancy and long COVID, were confirmed. This study provides insights for designing future effective vaccination programs for emerging vaccine-preventable infectious X diseases.

Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions.

BACKGROUND: Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions. OBJECTIVE: To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy. STUDY TYPE: Prospective. POPULATION: 137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years). FIELD STRENGTH/SEQUENCE: T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system. ASSESSMENT: The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusion f 1 $$ {f}_1 $$ , hindered diffusion f 2 $$ {f}_2 $$ , and free diffusion f 3 $$ {f}_3 $$ ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination. STATISTICAL TESTS: Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant. RESULTS: The f 1 $$ {f}_1 $$ , SUVmax were significantly higher, and f 3 $$ {f}_3 $$ , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC ( f 3 $$ {f}_3 $$ ) > AUC ( f 1 $$ {f}_1 $$ ) > AUC (ADC) > AUC ( f 2 $$ {f}_2 $$ ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging. CONCLUSION: RSI-derived parameters ( f 1 $$ {f}_1 $$ , f 3 $$ {f}_3 $$ ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility of f 2 $$ {f}_2 $$ was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy. TECHNICAL EFFICACY: Stage 2.

Assessment of Lung Nodule Detection and Lung CT Screening Reporting and Data System Classification Using Zero Echo Time Pulmonary MRI.

BACKGROUND: The detection rate of lung nodules has increased considerably with CT as the primary method of examination, and the repeated CT examinations at 3 months, 6 months or annually, based on nodule characteristics, have increased the radiation exposure of patients. So, it is urgent to explore a radiation-free MRI examination method that can effectively address the challenges posed by low proton density and magnetic field inhomogeneities. PURPOSE: To evaluate the potential of zero echo time (ZTE) MRI in lung nodule detection and lung CT screening reporting and data system (lung-RADS) classification, and to explore the value of ZTE-MRI in the assessment of lung nodules. STUDY TYPE: Prospective. POPULATION: 54 patients, including 21 men and 33 women. FIELD STRENGTH/SEQUENCE: Chest CT using a 16-slice scanner and ZTE-MRI at 3.0T based on fast gradient echo. ASSESSMENT: Nodule type (ground-glass nodules, part-solid nodules, and solid nodules), lung-RADS classification, and nodule diameter (manual measurement) on CT and ZTE-MRI images were recorded. STATISTICAL TESTS: The percent of concordant cases, Kappa value, intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman. The p-value <0.05 is considered significant. RESULTS: A total of 54 patients (age, 54.8 ± 11.9 years; 21 men) with 63 nodules were enrolled. Compared with CT, the total nodule detection rate of ZTE-MRI was 85.7%. The intermodality agreement of ZTE-MRI and CT lung nodules type evaluation was substantial (Kappa = 0.761), and the intermodality agreement of ZTE-MRI and CT lung-RADS classification was moderate (Kappa = 0.592). The diameter measurements between ZTE-MRI and CT showed no significant difference and demonstrated a high degree of interobserver (ICC = 0.997-0.999) and intermodality (ICC = 0.956-0.985) agreements. DATA CONCLUSION: The measurement of nodule diameter by pulmonary ZTE-MRI is similar to that by CT, but the ability of lung-RADS to classify nodes from MRI images still requires further research. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer.

OBJECTIVES: To develop an [18F]FDG PET/3D-UTE model based on clinical factors, three-dimensional ultrashort echo time (3D-UTE), and PET radiomics features via machine learning for the assessment of lymph node (LN) status in non-small cell lung cancer (NSCLC). METHODS: A total of 145 NSCLC patients (training, 101 cases; test, 44 cases) underwent whole-body [18F]FDG PET/CT and chest [18F]FDG PET/MRI were enrolled. Preoperative clinical factors and 3D-UTE, CT, and PET radiomics features were analyzed. The Mann-Whitney U test, LASSO regression, and SelectKBest were used for feature extraction. Five machine learning algorithms were used to establish prediction models, which were evaluated by the area under receiver-operator characteristic (ROC), DeLong test, calibration curves, and decision curve analysis (DCA). RESULTS: A prediction model based on random forest, consisting of four clinical factors, six 3D-UTE, and six PET radiomics features, was used as the final model for PET/3D-UTE. The AUCs of this model were 0.912 and 0.791 in the training and test sets, respectively, which not only showed different degrees of improvement over individual models such as clinical, 3D-UTE, and PET (AUC-training = 0.838, 0.834, and 0.828, AUC-test = 0.756, 0.745, and 0.768, respectively) but also achieved the similar diagnostic efficacy as the optimal PET/CT model (AUC-training = 0.890, AUC-test = 0.793). The calibration curves and DCA indicated good consistency (C-index, 0.912) and clinical utility of this model, respectively. CONCLUSION: The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using machine learning methods could noninvasively assess the LN status of NSCLC. CLINICAL RELEVANCE STATEMENT: A machine learning model of 18F-fluorodeoxyglucose positron emission tomography/ three-dimensional ultrashort echo time could noninvasively assess the lymph node status of non-small cell lung cancer, which provides a novel method with less radiation burden for clinical practice. KEY POINTS: • The 3D-UTE radiomics model using the PLS-DA classifier was significantly associated with LN status in NSCLC and has similar diagnostic performance as the clinical, CT, and PET models. • The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using the RF classifier could noninvasively assess the LN status of NSCLC and showed improved diagnostic performance compared to the clinical, 3D-UTE, and PET models. • In the assessment of LN status in NSCLC, the [18F]FDG PET/3D-UTE model has similar diagnostic efficacy as the [18F]FDG PET/CT model that incorporates clinical factors and CT and PET radiomics features.

Performance of node reporting and data system (node-RADS): a preliminary study in cervical cancer.

BACKGROUND: Node Reporting and Data System (Node-RADS) was proposed and can be applied to lymph nodes (LNs) across all anatomical sites. This study aimed to investigate the diagnostic performance of Node-RADS in cervical cancer patients. METHODS: A total of 81 cervical cancer patients treated with radical hysterectomy and LN dissection were retrospectively enrolled. Node-RADS evaluations were performed by two radiologists on preoperative MRI scans for all patients, both at the LN level and patient level. Chi-square and Fisher's exact tests were employed to evaluate the distribution differences in size and configuration between patients with and without LN metastasis (LNM) in various regions. The receiver operating characteristic (ROC) and the area under the curve (AUC) were used to explore the diagnostic performance of the Node-RADS score for LNM. RESULTS: The rates of LNM in the para-aortic, common iliac, internal iliac, external iliac, and inguinal regions were 7.4%, 9.3%, 19.8%, 21.0%, and 2.5%, respectively. At the patient level, as the NODE-RADS score increased, the rate of LNM also increased, with rates of 26.1%, 29.2%, 42.9%, 80.0%, and 90.9% for Node-RADS scores 1, 2, 3, 4, and 5, respectively. At the patient level, the AUCs for Node-RADS scores > 1, >2, > 3, and > 4 were 0.632, 0.752, 0.763, and 0.726, respectively. Both at the patient level and LN level, a Node-RADS score > 3 could be considered the optimal cut-off value with the best AUC and accuracy. CONCLUSIONS: Node-RADS is effective in predicting LNM for scores 4 to 5. However, the proportions of LNM were more than 25% at the patient level for scores 1 and 2, which does not align with the expected very low and low probability of LNM for these scores.

Blood-labyrinth barrier breakdown in Meniere's disease.

OBJECTIVE: We compared the signal intensity ratio (SIR) of the cochlear basal turn between Meniere's disease and healthy controls to investigate potential damage of the blood-labyrinth barrier in Meniere's disease. METHODS: Thirty patients diagnosed with unilateral definite Meniere's disease and 24 healthy controls were enrolled. 3D-FLAIR scan was conducted to assess the grades of endolymphatic hydrops in Meniere's patients while measuring the SIR of cochlear basal turns in both groups. The differences of bilateral SIR between Meniere's disease and healthy control were compared, and the correlation between the SIR on affected ear in Meniere's disease and the grades of cochlear and vestibular hydrops were analyzed. RESULTS: SIR of affected ear in Meniere's disease exhibited significant increase compared to that of unaffected ear. No significant difference was observed in SIR between the two ears in the healthy control. Furthermore, the SIR of unaffected side in Meniere's disease was higher than that of both ears in healthy controls. The SIR in affected ear of Meniere's disease exhibited positive correlation with hydrops in both cochlea and vestibula. CONCLUSION: The permeability of blood-labyrinth barrier is increased in Meniere's disease, in combination with the typical criteria of Meniere's disease it may be a good biological marker. Destruction of blood-labyrinth barrier may be one of the causes of endolymphatic hydrops in Meniere's disease.

Understanding the impact of chronic diseases on COVID-19 vaccine hesitancy using propensity score matching: Internet-based cross-sectional study.

AIMS AND OBJECTIVES: To investigate whether chronic diseases are associated with higher COVID-19 vaccine hesitancy and explore factors that influence COVID-19 vaccine hesitancy in patients with chronic diseases. BACKGROUND: Vaccine hesitancy has been acknowledged as one of the greatest hazards to public health. However, little information is available about COVID-19 vaccine hesitancy among patients with chronic diseases who may be more susceptible to COVID-19 infection, severe disease or death. METHODS: From 6 to 9 August 2021, we performed an internet-based cross-sectional survey with 22,954 participants (14.78% participants with chronic diseases). Propensity score matching with 1:1 nearest neighbourhood was used to reduce confounding factors between patients with chronic diseases and the general population. Using a multivariable logistic regression model, the factors impacting COVID-19 vaccine hesitancy were identified among patients with chronic diseases. RESULTS: Both before and after propensity score matching, patients with chronic diseases had higher COVID-19 vaccine hesitancy than the general population. In addition, self-reported poor health, multiple chronic diseases, lower sociodemographic backgrounds and lower trust in nurses and doctors were associated with COVID-19 vaccine hesitancy among patients with chronic diseases. CONCLUSIONS: Patients with chronic diseases were more hesitant about the COVID-19 vaccine. Nurses should focus on patients with chronic diseases with poor health conditions, low socioeconomic backgrounds and low trust in the healthcare system. RELEVANCE TO CLINICAL PRACTICE: Clinical nurses are recommended to not only pay more attention to the health status and sociodemographic characteristics of patients with chronic diseases but also build trust between nurses and patients by improving service levels and professional capabilities in clinical practice. PATIENT OR PUBLIC CONTRIBUTION: Patients or the public were not involved in setting the research question, the outcome measures, or the design or implementation of the study. However, all participants were invited to complete the digital informed consent and questionnaires.

BcABF1 Plays a Role in the Feedback Regulation of Abscisic Acid Signaling via the Direct Activation of BcPYL4 Expression in Pakchoi.

Abscisic acid-responsive element-binding factor 1 (ABF1), a key transcription factor in the ABA signal transduction process, regulates the expression of downstream ABA-responsive genes and is involved in modulating plant responses to abiotic stress and developmental processes. However, there is currently limited research on the feedback regulation of ABF1 in ABA signaling. This study delves into the function of BcABF1 in Pakchoi. We observed a marked increase in BcABF1 expression in leaves upon ABA induction. The overexpression of BcABF1 not only spurred Arabidopsis growth but also augmented the levels of endogenous IAA. Furthermore, BcABF1 overexpression in Arabidopsis significantly decreased leaf water loss and enhanced the expression of genes associated with drought tolerance in the ABA pathway. Intriguingly, we found that BcABF1 can directly activate BcPYL4 expression, a critical receptor in the ABA pathway. Similar to BcABF1, the overexpression of BcPYL4 in Arabidopsis also reduces leaf water loss and promotes the expression of drought and other ABA-responsive genes. Finally, our findings suggested a novel feedback regulation mechanism within the ABA signaling pathway, wherein BcABF1 positively amplifies the ABA signal by directly binding to and activating the BcPYL4 promoter.

Reassembled saturation transfer (REST) MR images at 2 B1 values for in vivo exchange-dependent imaging of amide and nuclear Overhauser enhancement.

PURPOSE: Design an efficient CEST scheme for exchange-dependent images with high contrast-to-noise ratio. THEORY: Reassembled saturation transfer (REST) signals were defined as Δ $$ \Delta $$ r.Z = r.Zref - r.ZCEST and the reassembled exchange-dependen magnetization transfer ratio r.MTRRex  = r.1/Zref - r.1/ZCEST , utilizing the averages over loosely sampled reference frequency offsets as Zref and over densely sampled target offsets as ZCEST . Using r.MTRRex measured under 2 B1,sat values, exchange rate could be estimated. METHODS: The REST approach was optimized and assessed quantitatively by simulations for various exchange rates, pool concentration, and water T1 . In vivo evaluation was performed on ischemic rat brains at 7 Tesla and human brains at 3 Tesla, in comparison with conventional asymmetrical analysis, Lorentzian difference (LD), an MTRRex_ LD. RESULTS: For a broad choice of Δ ω ref $$ \Delta {\omega}_{ref} $$ ranges and numbers, Δr.Z and r.MTRRex exhibited comparable quantification features with conventional LD and MTRRex _LD, respectively, when B1,sat  ≤ 1 µT. The subtraction of 2 REST values under distinct B1,sat values showed linear relationships with exchange rate and obtained immunity to field inhomogeneity and variation in MT and water T1 . For both rat and human studies, REST images exhibited similar contrast distribution to MTRRex _LD, with superiority in contrast-to-noise ratio and acquisition efficiency. Compared with MTRRex _LD, 2-B1,sat subtraction REST images displayed better resistance to B1 inhomogeneity, with more specific enhanced regions. They also showed higher signals for amide than for nuclear Overhauser enhancement effect in human brain, presumably reflecting the higher increment from faster-exchanging species as B1,sat increased. CONCLUSION: Featuring high contrast-to-noise ratio efficiency, REST could be a practical exchange-dependent approach readily applicable to either retrospective Z-spectra analysis or perspective 6-offset acquisition.

Clinical observation of neutralizing antibody DXP-604 for treatment critical COVID-19 patients infected with SARS-CoV-2 Delta variant.

From January to March 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta (B.1.617.2) infection was prevalent in Yuzhou and Zhengzhou. DXP-604 is a broad-spectrum antiviral monoclonal antibody, which has excellent viral neutralization ability in vitro and a long half-life in vivo, with good biosafety and tolerability. Preliminary results showed that DXP-604 can accelerate recovery from Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 Delta variant in hospitalized patients with mild to moderate clinical symptoms. However, the efficacy of DXP-604 has not been fully studied in high-risk severe patients. Here, we prospectively enrolled 27 high-risk patients, two groups were divided, in addition to receiving standard of care (SOC), 14 of them additionally received the neutralizing antibody DXP-604 therapy, and another 13 intensive care unit (ICU) patients simultaneously underwent SOC as a control group matched for age, gender, and clinical type. The results revealed lower C-reactive protein, interleukin-6, lactic dehydrogenase and neutrophil counts, and higher lymphocyte and monocyte counts from Day 3 post-DXP-604 treatment compared with SOC treatment. Besides, thoracic CT images showed improvements in lesion areas and degrees, along with changes in blood inflammatory factors. Moreover, DXP-604 reduced the invasive mechanical ventilation and mortality of high-risk SARS-CoV-2 infected patients. The ongoing clinical trials of DXP-604 neutralizing antibody will clarify its utility as a new attractive countermeasure for high-risk COVID-19.

Fibroadipose vascular anomaly: a clinicopathological study of 75 cases.

AIMS: Fibroadipose vascular anomaly (FAVA) is a complex vascular malformation that is likely to be under-recognised. In this study we aimed to report the pathological features and somatic PIK3CA mutations associated with the most common clinicopathological features. METHODS AND RESULTS: Cases were identified by reviewing the lesions resected from patients with FAVA registered at our Haemangioma Surgery Centre and unusual intramuscular vascular anomalies in our pathology database. There were 23 males and 52 females, who ranged in age from 1 to 51 years. Most cases occurred in the lower extremities (n = 62). The majority of the lesions were intramuscular, with a few disrupting the overlying fascia and involving subcutaneous fat (19 of 75), and a minority of the cases had cutaneous vascular stains (13 of 75). Histopathologically, the lesion was composed of anomalous vascular components that were intertwined with mature adipocytic and dense fibrous tissues and vascular components with: (a) clusters of thin-walled channels, some with blood-filled nodules and others with thin walls resembling pulmonary alveoli; (b) numerous small vessels (arteries, veins and indeterminate channels) - proliferative small blood vessels were often mixed with adipose tissue; (c) larger abnormal venous channels usually irregularly and sometimes excessively muscularised; (d) lymphoid aggregates or lymphoplasmacytic aggregates were usually observed; and (e) lymphatic malformations were sometimes seen as minor elements. All patients had their lessons subjected to PCR, and 53 patients had somatic PIK3CA mutations (53 of 75). CONCLUSIONS: FAVA is a slow-flow vascular malformation with specific clinicopathological and molecular characteristics. Its recognition is fundamental for its clinical/prognostic implications and for targeted therapy.

Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.

PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult to widely use. Therefore, we attempt to utilize high-quality images generated by uEXPLORER to optimize the quality of images from short-axis PET scanners through deep learning technology while controlling costs. METHODS: The experiments were conducted using PET images of three anatomical locations (brain, lung, and abdomen) from 335 patients. To simulate PET images from different axes, two protocols were used to obtain PET image pairs (each patient was scanned once). For low-quality PET (LQ-PET) images with a 320-mm AFOV, we applied a 300-mm FOV for brain reconstruction and a 500-mm FOV for lung and abdomen reconstruction. For high-quality PET (HQ-PET) images, we applied a 1940-mm AFOV during the reconstruction process. A 3D Unet was utilized to learn the mapping relationship between LQ-PET and HQ-PET images. In addition, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were employed to evaluate the model performance. Furthermore, two nuclear medicine doctors evaluated the image quality based on clinical readings. RESULTS: The generated PET images of the brain, lung, and abdomen were quantitatively and qualitatively compatible with the HQ-PET images. In particular, our method achieved PSNR values of 35.41 ± 5.45 dB (p < 0.05), 33.77 ± 6.18 dB (p < 0.05), and 38.58 ± 7.28 dB (p < 0.05) for the three beds. The overall mean SSIM was greater than 0.94 for all patients who underwent testing. Moreover, the total subjective quality levels of the generated PET images for three beds were 3.74 ± 0.74, 3.69 ± 0.81, and 3.42 ± 0.99 (the highest possible score was 5, and the minimum score was 1) from two experienced nuclear medicine experts. Additionally, we evaluated the distribution of quantitative standard uptake values (SUV) in the region of interest (ROI). Both the SUV distribution and the peaks of the profile show that our results are consistent with the HQ-PET images, proving the superiority of our approach. CONCLUSION: The findings demonstrate the potential of the proposed technique for improving the image quality of a PET scanner with a 320 mm or even shorter AFOV. Furthermore, this study explored the potential of utilizing uEXPLORER to achieve improved short-axis PET image quality at a limited economic cost, and computer-aided diagnosis systems that are related can help patients and radiologists.

Amide Proton Transfer-Weighted Imaging and Multiple Models Intravoxel Incoherent Motion-Based 18 F-FDG PET/MRI for Predicting Progression-Free Survival in Non-Small Cell Lung Cancer.

BACKGROUND: Amide proton transfer-weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18 F-FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non-small cell lung cancer (NSCLC) still needs to be further explored. PURPOSE: To determine whether pretreatment APTWI, mono-, bi-, and stretched-exponential model IVIM, and 18 F-FDG PET-derived parameters of the primary lesion may be associated with progression-free survival (PFS) in NSCLC. STUDY TYPE: Prospective. POPULATION: Seventy-seven patients (mean age, 62 years, range, 20-81 years) with 37 men and 40 women were included. FIELD STRENGTH/SEQUENCE: 3.0 T 18 F-FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin-echo sequences with magnetization transfer pulses for APTWI. ASSESSMENT: Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow-up was 18 months, range, 4-27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand , D, D*, f, DDC, and α), and 18 F-FDG PET (SUVmax , MTV, and TLG) parameters were recorded. STATISTICAL TESTS: Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log-rank test. A P value <0.05 was considered statistically significant. RESULTS: Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C-index of 0.895 (95% CI: 0.839-0.951), which was significantly superior to each of the above predictors alone (C-index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log-rank test results showed a significant difference in PFS between the high- and low-risk groups. DATA CONCLUSION: APTWI and multiple models IVIM based 18 F-FDG PET/MRI can be used for PFS assessment in NSCLC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Development and validation of the OSASH score to predict overall survival of hepatocellular carcinoma after surgical resection: a dual-institutional study.

OBJECTIVE: To develop and validate a risk score based on preoperative clinical-radiological parameters for predicting overall survival (OS) in patients undergoing surgical resection for hepatocellular carcinoma (HCC). METHODS: From July 2010 to December 2021, consecutive patients with surgically-proven HCC who underwent preoperative contrast-enhanced MRI were retrospectively enrolled. A preoperative OS risk score was constructed in the training cohort using a Cox regression model and validated in a propensity score-matched internal validation cohort and an external validation cohort. RESULTS: A total of 520 patients were enrolled, among whom 210, 210, and 100 patients were from the training, internal validation, and external validation cohorts, respectively. Independent predictors for OS included incomplete tumor "capsule," mosaic architecture, tumor multiplicity, and serum alpha-fetoprotein, which were incorporated into the "OSASH score." The C-index the OSASH score was 0.85, 0.81, and 0.62 in the training, internal, and external validation cohorts, respectively. Using 32 as the cutoff point, the OSASH score stratified patients into prognostically distinct low- and high-risk groups among all study cohorts and six subgroups (all p < 0.05). Furthermore, patients with BCLC stage B-C HCC and OSASH-low risk achieved comparable OS to that of patients with BCLC stage 0-A HCC and OSASH-high risk in the internal validation cohort (5-year OS rates, 74.7 vs. 77.8%; p = 0.964). CONCLUSION: The OSASH score may help predict OS in HCC patients undergoing hepatectomy and identify potential surgical candidates among those with BCLC stage B-C HCC. CLINICAL RELEVANCE STATEMENT: By incorporating three preoperative MRI features and serum AFP, the OSASH score may help predict postsurgical overall survival in patients with hepatocellular carcinoma and identify potential surgical candidates among those with BCLC stage B and C HCC. KEY POINTS: • The OSASH score incorporating three MRI features and serum AFP can be used to predict OS in HCC patients who received curative-intent hepatectomy. • The score stratified patients into prognostically distinct low- and high-risk strata in all study cohorts and six subgroups. • Among patients with BCLC stage B and C HCC, the score identified a subgroup of low-risk patients who achieved favorable outcomes after surgery.

Expert consensus on oncological [18F]FDG total-body PET/CT imaging (version 1).

BACKGROUND: [18F]FDG imaging on total-body PET/CT (TB PET/CT) scanners, with improved sensitivity, offers new potentials for cancer diagnosis, staging, and radiation treatment planning. This consensus provides the protocols for clinical practices with a goal of paving the way for future studies with the total-body scanners in oncological [18F]FDG TB PET/CT imaging. METHODS: The consensus was summarized based on the published guidelines and peer-reviewed articles of TB PET/CT in the literature, along with the opinions of the experts from major research institutions with a total of 40,000 cases performed on the TB PET/CT scanners. RESULTS: This consensus describes the protocols for routine and dynamic [18F]FDG TB PET/CT scanning focusing on the reduction of imaging acquisition time and FDG injected activity, which may serve as a reference for research and clinic oncological PET/CT studies. CONCLUSION: This expert consensus focuses on the reduction of acquisition time and FDG injected activity with a TB PET/CT scanner, which may improve the patient throughput or reduce the radiation exposure in daily clinical oncologic imaging. KEY POINTS: • [18F]FDG-imaging protocols for oncological total-body PET/CT with reduced acquisition time or with different FDG activity levels have been summarized from multicenter studies. • Total-body PET/CT provides better image quality and improved diagnostic insights. • Clinical workflow and patient management have been improved.

Deep learning-based dynamic PET parametric Ki image generation from lung static PET.

OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric Ki provides better quantification and improve specificity for cancer detection. However, parametric imaging is difficult to implement clinically due to the long acquisition time (~ 1 h). We propose a dynamic parametric imaging method based on conventional static PET using deep learning. METHODS: Based on the imaging data of 203 participants, an improved cycle generative adversarial network incorporated with squeeze-and-excitation attention block was introduced to learn the potential mapping relationship between static PET and Ki parametric images. The image quality of the synthesized images was qualitatively and quantitatively evaluated by using several physical and clinical metrics. Statistical analysis of correlation and consistency was also performed on the synthetic images. RESULTS: Compared with those of other networks, the images synthesized by our proposed network exhibited superior performance in both qualitative and quantitative evaluation, statistical analysis, and clinical scoring. Our synthesized Ki images had significant correlation (Pearson correlation coefficient, 0.93), consistency, and excellent quantitative evaluation results with the Ki images obtained in standard dynamic PET practice. CONCLUSIONS: Our proposed deep learning method can be used to synthesize highly correlated and consistent dynamic parametric images obtained from static lung PET. KEY POINTS: • Compared with conventional static PET, dynamic PET parametric Ki imaging has been shown to provide better quantification and improved specificity for cancer detection. • The purpose of this work was to develop a dynamic parametric imaging method based on static PET images using deep learning. • Our proposed network can synthesize highly correlated and consistent dynamic parametric images, providing an additional quantitative diagnostic reference for clinicians.

Progressive increase of high-frequency EEG oscillations during meditation is associated with its trait effects on heart rate and proteomics: a study on the Tibetan Buddhist.

Meditation has been a spiritual and healing practice in the East for thousands of years. However, the neurophysiologic mechanisms underlying its traditional form remain unclear. In this study, we recruited a large sample of monks (n = 73) who practice Tibetan Buddhist meditation and compared with meditation-naive local controls (n = 30). Their electroencephalography (EEG) and electrocardiogram signals were simultaneously recorded and blood samples were collected to investigate the integrative effects of Tibetan Buddhist on brain, heart, and proteomics. We found that the EEG activities in monks shifted to a higher frequency from resting to meditation. Meditation starts with decrease of the (pre)frontal delta activity and increase of the (pre)frontal high beta and gamma activity; while at the deep meditative state, the posterior high-frequency activity was also increased, and could be specified as a biomarker for the deep meditation. The state increase of posterior high-frequency EEG activity was significantly correlated with the trait effects on heart rate and nueropilin-1 in monks, with the source of brain-heart correlation mainly locating in the attention and emotion networks. Our study revealed that the effects of Tibetan Buddhist meditation on brain, heart, and proteomics were highly correlated, demonstrating meditation as an integrative body-mind training.