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Abstract Background The relationship between variation in serum uric acid (SUA) levels and brain health is largely unknown. This study aimed to examine the associations of long-term variability in SUA levels with neuroimaging metrics and cognitive function. Methods This study recruited 1111 participants aged 25–83 years from a multicenter, community-based cohort study. The SUA concentrations were measured every two years from 2006 to 2018. We measured the intraindividual SUA variability, including the direction and magnitude of change by calculating the slope value. The associations of SUA variability with neuroimaging markers (brain macrostructural volume, microstructural integrity, white matter hyperintensity, and the presence of cerebral small vessel disease) and cognitive function were examined using generalized linear models. Mediation analyses were performed to assess whether neuroimaging markers mediate the relationship between SUA variation and cognitive function. Results Compared with the stable group, subjects with increased or decreased SUA levels were all featured by smaller brain white matter volume (beta = − 0.25, 95% confidence interval [CI] − 0.39 to − 0.11 and beta = − 0.15, 95% CI − 0.29 to − 0.02). Participants with progressively increased SUA exhibited widespread disrupted microstructural integrity, featured by lower global fractional anisotropy (beta = − 0.24, 95% CI − 0.38 to − 0.10), higher mean diffusivity (beta = 0.16, 95% CI 0.04 to 0.28) and radial diffusivity (beta = 0.19, 95% CI 0.06 to 0.31). Elevated SUA was also associated with cognitive decline (beta = − 0.18, 95% CI − 0.32 to − 0.04). White matter atrophy and impaired brain microstructural integrity mediated the impact of SUA increase on cognitive decline. Conclusions It is the magnitude of SUA variation rather than the direction that plays a critical negative role in brain health, especially for participants with hyperuricemia. Smaller brain white matter volume and impaired microstructural integrity mediate the relationship between increased SUA level and cognitive function decline. Long-term stability of SUA level is recommended for maintaining brain health and preventing cognitive decline.

Abstract Objective Normal aging is associated with brain volume change, and brain segmentation can be performed within an acceptable scan time using synthetic magnetic resonance imaging (MRI). This study aimed to investigate the brain volume changes in healthy adult according to age and gender, and provide age‐ and gender‐specific reference values using synthetic MRI. Methods A total of 300 healthy adults (141 males, median age 48; 159 females, median age 50) were underwent synthetic MRI on 3.0 T. Brain parenchymal volume (BPV), gray matter volume (GMV), white matter volume (WMV), myelin volume (MYV), and cerebrospinal fluid volume (CSFV) were calculated using synthetic MRI software. These volumes were normalized by intracranial volume to normalized GMV (nGMV), normalized WMV (nWMV), normalized MYV (nMYV), normalized BPV (nBPV), and normalized CSFV (nCSFV). The normalized brain volumes were plotted against age in both males and females, and a curve fitting model that best explained the age dependence of brain volume was identified. The normalized brain volumes were compared between different age and gender groups. Results The approximate curves of nGMV, nWMV, nCSFV, nBPV, and nMYV were best fitted by quadratic curves. The nBPV decreased monotonously through all ages in both males and females, while the changes of nCSFV showed the opposite trend. The nWMV and nMYV in both males and females increased gradually and then decrease with age. In early adulthood (20s), nWMV and nMYV in males were lower and peaked later than that in females (p

Objective: Appropriate medical imaging is important for value-based care. We aim to evaluate the performance of generative pretrained transformer 4 (GPT-4), an innovative natural language processing model, providing appropriate medical imaging automatically in different clinical scenarios. Methods: Institutional Review Boards (IRB) approval was not required due to the use of nonidentifiable data. Instead, we used 112 questions from the American College of Radiology (ACR) Radiology-TEACHES Program as prompts, which is an open-sourced question and answer program to guide appropriate medical imaging. We included 69 free-text case vignettes and 43 simplified cases. For the performance evaluation of GPT-4 and GPT-3.5, we considered the recommendations of ACR guidelines as the gold standard, and then three radiologists analyzed the consistency of the responses from the GPT models with those of the ACR. We set a five-score criterion for the evaluation of the consistency. A paired t-test was applied to assess the statistical significance of the findings. Results: For the performance of the GPT models in free-text case vignettes, the accuracy of GPT-4 was 92.9%, whereas the accuracy of GPT-3.5 was just 78.3%. GPT-4 can provide more appropriate suggestions to reduce the overutilization of medical imaging than GPT-3.5 (t = 3.429, P = 0.001). For the performance of the GPT models in simplified scenarios, the accuracy of GPT-4 and GPT-3.5 was 66.5% and 60.0%, respectively. The differences were not statistically significant (t = 1.858, P = 0.070). GPT-4 was characterized by longer reaction times (27.1 s in average) and extensive responses (137.1 words on average) than GPT-3.5. Conclusion: As an advanced tool for improving value-based healthcare in clinics, GPT-4 may guide appropriate medical imaging accurately and efficiently.

Abstract Microstructural alterations in the brain networks of Parkinson’s disease (PD) patients are correlated with gait impairments. Evaluate microstructural alterations in the white matter (WM) fiber bundle tracts using neurite orientation dispersion and density imaging (NODDI) technique in PD versus healthy controls (HC). In this study, 24 PD patients and 29 HC were recruited. NODDI and high-resolution 3D structural images were acquired for each participant. The NODDI indicators, including the intracellular neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISO), were compared between the two groups. Diffusion-weighted (DW) images were preprocessed using MRtrix 3.0 software and the orientation distribution function to trace the main nerve fiber tracts in PD patients. Quantitative gait and clinical assessment scales were used to compare the medication “ON” and “OFF” states of PD patients. The NDI, ODI, and ISO values of the WM fiber bundles were significantly higher in PD patients compared to HC. Fiber bundles, including the anterior thalamic radiation, corticospinal tract, superior longitudinal fasciculus, forceps major, cingulum, and inferior longitudinal fasciculus, were found to be significantly affected in PD. The NDI changes of PD patients were well correlated with stride lengths in the “ON” state; ODI changes were correlated with the stride time in the “ON” and “OFF” states and ISO changes were correlated with the stride time and cadence in the “ON” state. In conclusion, combination of NODDI technique and gait parameters can help detect gait impairment in PD patients early and accurately.

Abstract Background The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition. Methods We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P

Using functional connectivity (FC) or effective connectivity (EC) alone cannot effectively delineate brain networks based on functional magnetic resonance imaging (fMRI) data, limiting the understanding of the mechanism of tinnitus and its treatment. Investigating brain FC is a foundational step in exploring EC. This study proposed a functionally guided EC (FGEC) method based on reinforcement learning (FGECRL) to enhance the precision of identifying EC between distinct brain regions. An actor–critic framework with an encoder–decoder model was adopted as the actor network. The encoder utilizes a transformer model; the decoder employs a bidirectional long short-term memory network with attention. An FGEC network was constructed for the enrolled participants per fMRI scan, including 65 patients with tinnitus and 28 control participants healthy at the enrollment time. After 6 months of sound therapy for tinnitus and prospective follow-up, fMRI data were acquired again and retrospectively categorized into an effective group (EG) and an ineffective group (IG) according to the treatment effect. Compared with FC and EC, the FGECRL method demonstrated better accuracy in discriminating between different groups, highlighting the advantage of FGECRL in identifying brain network features. For the FGEC network of the EG and IG per state (before and after treatment) and healthy controls, effective therapy is characterized by a similar pattern of FGEC network between patients with tinnitus after treatment and healthy controls. Deactivated information output in the motor network, somatosensory network, and medioventral occipital cortex may biologically indicate effective treatment. The maintenance of decreased EC in the primary auditory cortex may represent a failure of sound therapy, further supporting the Bayesian inference theory for tinnitus perception. The FGEC network can provide direct evidence for the mechanism of sound therapy in patients with tinnitus with distinct outcomes.

Abstract Objectives To explore changes in cerebral blood flow (CBF) and white matter in hemodialysis patients. Methods Thirty-three hemodialysis patients who underwent two brain MRI at an interval of three years and 33 age- and sex-matched healthy controls (HC) underwent structural and arterial spin-labeling MRI examinations. Intergroup differences in CBF in the gray matter, white matter, and whole matter, and regional white matter hyperintensities (WMH) were analyzed. Based on the changes in CBF between the baseline and follow-up groups, the hemodialysis patients were divided into two subgroups: an increased CBF group and a decreased CBF group. Differences in CBF and WMH between the subgroups and HC were analyzed. Results Patients undergoing hemodialysis exhibited increased cerebral watershed (CW) WMH, deep WMH, and periventricular WMH (P

Abstract Background The low absorption of x-rays in lung tissue and the poor resolution of conventional computed tomography (CT) limits its use to detect lung disease. However, x-ray dark-field imaging can sense the scattered x-rays deflected by the structures being imaged. This technique can facilitate the detection of small alveolar lesions that would be difficult to detect with conventional CT. Therefore, it may provide an alternative imaging modality to diagnose lung disease at an early stage. Methods Eight mice were inoculated with lung cancers simultaneously. Each time two mice were scanned using a grating-based dark-field CT on days 4, 8, 12, and 16 after the introduction of the cancer cells. The detectability index was calculated between nodules and healthy parenchyma for both attenuation and dark-field modalities. High-resolution micro-CT and pathological examinations were used to crosscheck and validate our results. Paired t-test was used for comparing the ability of dark-field and attenuation modalities in pulmonary nodule detection. Results The nodules were shown as a signal decrease in the dark-field modality and a signal increase in the attenuation modality. The number of nodules increased from day 8 to day 16, indicating disease progression. The detectability indices of dark-field modality were higher than those of attenuation modality (p = 0.025). Conclusions Compared with the standard attenuation CT, the dark-field CT improved the detection of lung nodules. Relevance statement Dark-field CT has a higher detectability index than conventional attenuation CT in lung nodule detection. This technique could improve the early diagnosis of lung cancer. Key points • Lung cancer progression was observed using x-ray dark-field CT. • Dark-field modality complements with attenuation modality in lung nodule detection. • Dark-field modality showed a detectability index higher than that attenuation in nodule detection. Graphical Abstract

Haloxylon ammodendron is a pioneering tree species for windbreak and sand fixation and improving the ecological environment. However, its cultivation faces substantial challenges, including low survival rates and slow growth. Designing a scientifically reasonable irrigation method is crucial to ensure the survival and healthy growth of H. ammodendron. Therefore, a field cylinder experiment with two drip irrigation methods — vertical tube surface drip irrigation (PSDI) and traditional surface drip irrigation (TSDI) — was conducted from May 2022 to May 2023 to explore the effects of irrigation methods on H. ammodendron growth. Additionally, three tube diameters (D = 90, 110, and 160 mm) and three burial depths (B = 10, 15, and 20 cm) were designed in PSDI to reveal the response of H. ammodendron growth to different tube parameters. The results showed that PSDI improved soil moisture content in the 5–40 cm layer while reducing soil temperature, demonstrating a more pronounced effect on water retention and temperature control. Throughout the growing season, when each indicator reached its maximum value, PSDI resulted in increases in plant height, stem diameter, crown width, new shoot length, and number of new shoots by 61.3 %, 45.1 %, 44.4 %, 37.8 %, and 24.6 % compared to TSDI, respectively. Additionally, PSDI increased total fresh and dry weights, aboveground fresh and dry weights, and underground fresh and dry weights by 30.5 % and 39.3 %, 31.9 % and 42.5 %, and 26.4 % and 27.6 %, respectively, while decreasing the root-to-shoot ratio by 15.4 %. The optimal growth indicators and biomass were achieved with a tube diameter of 160 mm and a burial depth of 15 cm under PSDI. On this basis, an empirical model to predict the growth dynamics of H. ammodendron was developed and showed consistency with measured values. These findings provide a theoretical basis for optimizing PSDI design and its application in plant sand-fixation engineering.

Background: Retinal health indices were suggested to be related to psychopathological symptoms, such as depressive symptoms. However, large-scale studies using optical coherence tomography (OCT) are missing to investigate the associations among them. Methods: In the META-KLS cohort study, 1456 participants (mean age [standard deviation]= 54.6 [11.91] years; n= 680 [47.8%] women) completed the Patient Health Questionnaire (PHQ-9) to measure depressive symptoms and underwent OCT. Poor-quality OCTs and multivariate outliers were excluded, and principal component analysis was performed to obtain retinal health indices separately for macular (n= 930) and optic nerve head (ONH) thicknesses (n= 800). Linear regressions were run controlling for covariates. Exploratory interaction models were run with demographic, lifestyle and health markers. Results: Although there were no direct significant associations between the retinal indices and depressive symptoms (macular: B= −0.05, 95% CI= [-0.15, 0.05], p= 0.32; ONH index: B= -0.02, 95% CI= [-0.11, 0.08], p= 0.71), their associations were moderated by demographic and health factors, e.g., C-reactive protein (CRP) (macular index: B= −0.03, 95% CI= [-0.05, −0.01], p= 0.002; ONH index: B= 0.05, 95% CI= [0.02, 0.08], p= 0.002). Limitations: Study was cross-sectional and there were no functional assessments of vision. Conclusions: In a large cohort, we observed associations between retinal indices and self-reported depressive symptoms depending on demographic and health factors, notably CRP. Following up, the study will investigate the prospective prediction of retinal health on depressive symptoms, especially in persons who may have chronic inflammation.

Abstract Objective Using two three-dimensional U-Net architectures for myocardium structure extraction and a distance transformation algorithm specifically for the left circumflex artery, we have designed a fully automated algorithm for coronary artery labeling in coronary computed tomography angiography (CCTA) images. Methods In this retrospective analysis, a cohort of 157 patients who had undergone coronary computed tomography angiography (CCTA) was included. An automated coronary artery labeling algorithm was developed using a distance transformation approach to delineate the anatomical segments along the centerlines extracted from the CCTA images. A total of 16 segments were successfully identified and labeled. The algorithm’s outcomes were recorded and reviewed by three experts, and the performance of segment detection and labeling was assessed. Additionally, the level of agreement in manually labeled segments between two experts was quantified. Results When comparing the labels generated by the experts with those produced by the algorithm, it was necessary to modify or eliminate 117 labels (5.4%) out of 2180 segments assigned by the algorithm. The overall accuracy for label presence was 96.2%, with an average overlap of 94.0% between the expert reference and algorithm-generated labels. Furthermore, the average agreement rate between the two experts stood at 95.0%. Conclusions Based on the labels of the clinical experts, the proposed deep learning algorithm exhibits high accuracy for automatic labeling. Therefore, our proposed method exhibits promising results for the automatic labeling of the coronary arteries and will alleviate the burden on radiologists in the near future.

Abstract Purpose To compare the diagnostic sensitivity of ultra-high-resolution computed tomography (U-HRCT) and HRCT in isolated fenestral otosclerosis (IFO). Methods A retrospective analysis was conducted on 85 patients (85 ears) diagnosed with IFO between October 2020 and November 2022. U-HRCT (0.1 mm thickness) was performed for 20 ears, HRCT (0.67 mm thickness) for 45 ears, and both for 20 ears. The images were evaluated by general radiologists and neuroradiologists who were blinded to the diagnosis and surgical information. The diagnostic sensitivity of U-HRCT and HRCT for detecting IFO was compared between the two groups. Results Excellent inter-observer agreement existed between the two neuroradiologists (Cohen’s κ coefficient 0.806, 95% CI 0.692–0.920), with good agreement between the general radiologists (Cohen’s κ coefficient 0.680, 95% CI 0.417–0.943). U-HRCT had a sensitivity of 100% (40/40 ears) for neuroradiologists and 87.5% (35/40 ears) for general radiologists, significantly higher than HRCT (89.2% [58/65 ears] for neuroradiologists; 41.5% [27/65 ears] for general radiologists) (p = 0.042, p′

Abstract Background Bulimia nervosa (BN) is an eating disorder characterized by recurrent binge eating and compensatory behaviors. The thalamus plays a crucial role in the neural circuitry related to eating behavior and needs to be further explored in BN. Methods In this study, 49 BN patients and 44 healthy controls (HCs) were recruited. We applied the fractional amplitude of low-frequency fluctuation to investigate regional brain activity in the thalamus and functional connectivity (FC) to examine the synchronization of activity between thalamic subregions and other brain regions in both groups. All results underwent false discovery rate (p

Abstract Background Osseous changes of the temporomandibular joint (TMJ) are related to the progression of temporomandibular disorders (TMD), and computed tomography (CT) plays a vital role in disease evaluation. Objective The aims of this study were to evaluate the image quality and diagnostic value of ultra-high-resolution CT (U-HRCT) in TMD compared to cone-beam CT (CBCT). Methods TMD patients who underwent both CBCT and U-HRCT between November 2021 and September 2022 were retrospectively included. Image quality scores were assigned for four osseous structures (the cortical and trabecular bones of the condyle, articular eminence, and glenoid fossa) by two independent observers from Score 1 (unacceptable) to Score 5 (excellent). Diagnostic classification of TMD was categorized as follows: Class A (no evident lesion), Class B (indeterminate condition) and Class C (definitive lesion). Image quality scores and diagnostic classifications were compared between CBCT and U-HRCT. The Cohen’s Kappa test, Wilcoxon signed-rank test, Chi-square test and Fisher’s exact test were conducted for statistical analysis. Results Thirty TMD patients (median age, 30 years; interquartile range, 26–43 years; 25 females) with 60 TMJs were enrolled. Image quality scores were higher for U-HRCT than for CBCT by both observers (all Ps

Summary: Background: The relationship between the fluctuation in body size and brain health is poorly understood. This study aimed to examine the associations of long-term variability in body mass index (BMI) and waist-to-hip ratio (WHR) with neuroimaging metrics that approximate brain health. Methods: This cohort study recruited 1114 participants aged 25–83 years from a multicenter, community-based cohort study in China. We modeled the BMI and WHR trajectories of participants during 2006–2018 and assessed the BMI and WHR variability (direction and speed of change) by calculating the slope. Generalized linear models were applied to investigate the associations of BMI and WHR variability with MRI markers of brain tissue volume, white matter microstructural integrity, white matter hyperintensity (WMH), and cerebral small vessel disease (CSVD). Findings: Progressive weight gain during follow-up was associated with lower global fractional anisotropy (beta = −0.18, 95% confidence interval [CI] −0.34 to −0.02), higher mean diffusivity (beta = 0.15, 95% CI 0.01–0.30) and radial diffusivity (beta = 0.17, 95% CI 0.02–0.32). Weight loss was also associated with a lower burden of periventricular WMH (beta = −0.26, 95% CI −0.48 to −0.03) and a lower risk of moderate-to-severe basal ganglia enlarged perivascular spaces (BG-EPVS, odds ratio [OR] = 0.41, 95% CI 0.20–0.83). Among overweight populations, weight loss was linked with smaller volumes of WMH (beta = −0.47, 95% CI −0.79 to −0.15), periventricular WMH (beta = −0.57, 95% CI −0.88 to −0.26), and deep WMH (beta = −0.36, 95% CI −0.69 to −0.03), as well as lower risk of CSVD (OR = 0.22, 95% CI 0.08–0.62), lacune (OR = 0.12, 95% CI 0.01–0.91) and moderate-to-severe BG-EPVS (OR = 0.24, 95% CI 0.09–0.61). In adults with central obesity, WHR loss was positively associated with larger gray matter volume (beta = 0.50, 95% CI 0.11–0.89), hippocampus volume (beta = 0.62, 95% CI 0.15–1.09), and parahippocampal gyrus volume (beta = 0.85, 95% CI 0.34–1.37). The sex-stratification and age-stratification analyses revealed similar findings with the main results, with the pattern of associations significantly presented in the individuals at mid-life and late-life. Interpretation: Long-term stability of BMI level is essential for maintaining brain health. Progressive weight gain is associated with impaired white matter microstructural integrity. Weight and WHR losses are associated with improved general brain health. Our results contribute to a better understanding of the integrated associations between variations in obesity measures and brain health. Funding: This study was supported by grants No. 62171297 (Han Lv) and 61931013 (Zhenchang Wang) from the National Natural Science Foundation of China, No. 7242267 from the Beijing Natural Science Foundation (Han Lv), and No. [2015] 160 from the Beijing Scholars Program (Zhenchang Wang).

Background: The cumulative effect of body mass index (BMI) on brain health remains ill-defined. The effects of overweight on brain health across different age groups need clarification. We analyzed the effect of cumulative BMI on neuroimaging features of brain health in adults of different ages. Methods: This study was based on a multicenter, community-based cohort study. We modeled the trajectories of BMI over 16 years to evaluate cumulative exposure. Multimodality neuroimaging data were collected once for volumetric measurements of the brain macrostructure, white matter hyperintensity (WMH), and brain microstructure. We used a generalized linear model to evaluate the association between cumulative BMI and neuroimaging features. Two-sample Mendelian randomization analysis was performed using summary level of BMI genetic data from 681,275 individuals and neuroimaging genetic data from 33,224 individuals to analyze the causal relationships. Results: Clinical and neuroimaging data were obtained from 1,074 adults (25 to 83 years). For adults aged under 45 years, brain volume differences in participants with a cumulative BMI of >26.2 kg/m2 corresponded to 12.0 years [95% confidence interval (CI), 3.0 to 20.0] of brain aging. Differences in WMH were statistically substantial for participants aged over 60 years, with a 6.0-ml (95% CI, 1.5 to 10.5) larger volume. Genetic analysis indicated causal relationships between high BMI and smaller gray matter and higher fractional anisotropy in projection fibers. Conclusion: High cumulative BMI is associated with smaller brain volume, larger volume of white matter lesions, and abnormal microstructural integrity. Adults younger than 45 years are suggested to maintain their BMI below 26.2 kg/m2 for better brain health. Trial Registration: This study was registered on clinicaltrials.gov (Clinical Indicators and Brain Image Data: A Cohort Study Based on Kailuan Cohort; No. NCT05453877; https://clinicaltrials.gov/ct2/show/NCT05453877).

Objectives: To evaluate the efficacy and image processing time of the dynamic contrast-enhanced MRI (DCE-MRI) exchange model in liver fibrosis staging and compare it to the efficacy of magnetic resonance elastography (MRE). Methods: The subjects were 45 patients with nonalcoholic fatty liver disease (NAFLD) who underwent MRE and DCE-MRI in our hospital. Liver biopsy results were available for all patients. Spearman rank correlation coefficients were used to compare the correlations among MRE, DCE-MRI and liver fibrosis parameters. Quantitative DCE-MRI parameters, MRE-derived liver stiffness measurement (LSM), and the results of a combined DCE-MRI + MRE logistic regression model were compared in terms of the area under the receiver operating characteristic curve (AUC). We also compared the scanning and postprocessing times of the MRE and DCE-MRI techniques. Results: The correlation coefficients between the following parameters of interest and liver fibrosis were as follows: capillary permeability–surface area product (PS; DCE-MRI parameter), −0.761; portal blood flow (Fp; DCE-MRI parameter), −0.754; MRE-LSM, 0.835. Some DCE-MRI parameters (PS, Fp) had slightly greater AUC values than MRE-LSM for diagnosing the presence or absence of liver fibrosis, and the combined model had the highest AUC value for all stages except F4, but there was no significant difference in the diagnostic efficacy of the DCE-MRI, MRE, and combined models for any stage of fibrosis. The average scanning times for MRE and DCE-MRI were 17 s and 330 s, respectively, and the average postprocessing times were 45.5 s and 342.7 s, respectively. Conclusions: In the absence of MRE equipment, DCE-MRI represents an alternative technique. However, MRE is a quicker and simpler method for assessing fibrosis than DCE-MRI in the clinic.

Abstract Background The significance of liver metastasis (LM) in increasing the risk of death for postoperative colorectal cancer (CRC) patients necessitates innovative approaches to predict LM. Aim Our study presents a novel and significant contribution by developing an interpretable fusion model that effectively integrates both free‐text medical record data and structured laboratory data to predict LM in postoperative CRC patients. Methods We used a robust dataset of 1463 patients and leveraged state‐of‐the‐art natural language processing (NLP) and machine learning techniques to construct a two‐layer fusion framework that demonstrates superior predictive performance compared to single modal models. Our innovative two‐tier algorithm fuses the results from different data modalities, achieving balanced prediction results on test data and significantly enhancing the predictive ability of the model. To increase interpretability, we employed Shapley additive explanations to elucidate the contributions of free‐text clinical data and structured clinical data to the final model. Furthermore, we translated our findings into practical clinical applications by creating a novel NLP score‐based nomogram using the top 13 valid predictors identified in our study. Results The proposed fusion models demonstrated superior predictive performance with an accuracy of 80.8%, precision of 80.3%, recall of 80.5%, and an F1 score of 80.8% in predicting LMs. Conclusion This fusion model represents a notable advancement in predicting LMs for postoperative CRC patients, offering the potential to enhance patient outcomes and support clinical decision‐making.

Abstract Objective To explore the relationship of MRI morphology of primary rectal cancer with extramural vascular invasion (EMVI), metastasis and local recurrence. Materials and methods This retrospective study included 153 patients with rectal cancer. Imaging factors and histopathological index including nodular projection (NP), cord sign (CS) at primary tumor margin, irregular nodules (IN) of mesorectum, MRI-detected peritoneal reflection invasion (PRI), range of rectal wall invasion (RRWI), patterns and length of tumor growth, maximal extramural depth (EMD), histologically confirmed local node involvement (hLN), MRI T stage, MRI N stage, MRI-detected extramural vascular invasion (mEMVI) and histologically confirmed extramural vascular invasion (hEMVI) were evaluated. Determining the relationship between imaging factors and hEMVI, synchronous metastasis and local recurrence by univariate analysis and multivariable logistic regression, and a nomogram validated internally via Bootstrap self-sampling was constructed based on the latter. Results Thirty-eight cases of hEMVI, fourteen cases of synchronous metastasis and ten cases of local recurrence were observed among 52 NP cases. There were 50 cases of mEMVI with moderate consistency with hEMVI (Kappa = 0.614). NP, CS, EMD and mEMVI showed statistically significant differences in the negative and positive groups of hEMVI, synchronous metastasis, and local recurrence. Compared to patients with local mass growth, the rectal tumor with circular infiltration had been found to be at higher risk of synchronous metastasis and local recurrence (P

Abstract. Background:. The effect of arteriosclerotic intracranial arterial vessel wall enhancement (IAVWE) on downstream collateral flow found in vessel wall imaging (VWI) is not clear. Regardless of the mechanism underlying IAVWE on VWI, damage to the patient's nervous system caused by IAVWE is likely achieved by affecting downstream cerebral blood flow. The present study aimed to investigate the effect of arteriosclerotic IAVWE on downstream collateral flow. Methods:. The present study recruited 63 consecutive patients at the Second Hospital of Hebei Medical University from January 2021 to November 2021 with underlying atherosclerotic diseases and unilateral middle cerebral artery (MCA) M1-segment stenosis who underwent an magnetic resonance scan within 3 days of symptom onset. The patients were divided into 4 groups according to IAVWE and the stenosis ratio (Group 1, n = 17; Group 2, n = 19; Group 3, n = 13; Group 4, n = 14), and downstream collateral flow was analyzed using three-dimensional pseudocontinuous arterial spin labeling (3D-pCASL) and RAPID software. The National Institutes of Health Stroke Scale (NIHSS) scores of the patients were also recorded. Two-factor multivariate analysis of variance using Pillai's trace was used as the main statistical method. Results:. No statistically significant difference was found in baseline demographic characteristics among the groups. IAVWE, but not the stenosis ratio, had a statistically significant significance on the late-arriving retrograde flow proportion (LARFP), hypoperfusion intensity ratio (HIR), and NIHSS scores (F = 20.941, P

Abstract Background It is unclear whether dobutamine, commonly used clinically in echocardiography and short-term congestive heart failure treatment for promoting increased myocardial contractility, affects brain microcirculatory behavior. Cerebral microcirculation plays an important role in ensuring adequate oxygen transport. Therefore, we investigated the effects of dobutamine on cerebral hemodynamics. Methods Forty-eight healthy volunteers without cardiovascular or cerebrovascular disease underwent MRI to obtain cerebral blood flow (CBF) maps using 3D pseudocontinuous arterial spin labeling before and during the dobutamine stress test. Additionally, cerebrovascular morphology was obtained based on 3D-time-off-light (3D-TOF) magnetic resonance angiography (MRA). Electrocardiogram, heart rate (HR), respiration rate (RR), blood pressure, and blood oxygen were simultaneously recorded before and during dobutamine injection and during recovery (not during MRI). The anatomic features of the circle of Willis and the basilar artery (BA) diameter were assessed on MRA images by two radiologists with extensive neuroimaging experience. Binary logistic regression was used to test for the independent determinants of CBF changes. Results HR, RR, systolic (SBP), and diastolic blood pressure (DBP) significantly increased after dobutamine infusion. Blood oxygen levels remained similar. Compared to the CBF in the resting state, the CBF values exhibited significantly lower CBF levels in both grey matter and white matter. Furthermore, compared with the CBF in the resting state, that in the stress state was decreased in the anterior circulation, mainly in the frontal lobe (voxel level P

Straw strip burial in saline soil is an effective method for tideland reclamation in China, but optimal forms of straw strips for regulating soil water and salinity remain unclear. An indoor soil column test investigated the water and salt distribution in soil treated with four different straw forms under freshwater irrigation. The treatments included no straw layer (CK), straw stalks arranged longitudinally (T5), horizontally (T25), longitudinally combined horizontally in layers (T25+2.5), and randomly (T2.5). The results showed that compared to CK, T25, T5, and T25+2.5 significantly reduced the infiltration rate of irrigation water, leading to prolonged infiltration times. Wetting front curves under T5, T25+2.5, and T25 exhibited similar inverted “V” shapes, while CK and T2.5 showed fluctuating parallel lines. Water retention in the soil was higher under straw strip treatments (T5, T25, T25+2.5) and straw layer treatment (T2.5) compared to CK after 24 h of the first irrigation. T5 demonstrated the most effective salt removal, surpassing other treatments, with a desalination rate of 97.71%. Additionally, T5 had the highest salt leaching efficiency (SLE) in the 0–20 cm soil layer, recommending it as the optimal form for managing saline soils in crop production due to its simplicity and higher SLE. We found that buried straw strips reduced soil water infiltration rate and wetting front propulsion speed, increased soil water content and enhanced salt leaching efficiency in the saline soil. Our findings provide a basis for developing strategies that improve soil quality and irrigation efficiency, mitigate the effects of salinity on crop production, and ensure food security for a rapidly growing global population.

This study aimed to investigate the effect of the transverse sinus (TS) stenosis (TSS) position caused by arachnoid granulation on patients with venous pulsatile tinnitus (VPT) and to further identify the types of TSS that are of therapeutic significance for patients. Multiphysics interaction models of six patients with moderate TSS caused by arachnoid granulation and virtual stent placement in TSS were reconstructed, including three patients with TSS located in the middle segment of the TS (group 1) and three patients with TTS in the middle and proximal involvement segment of the TS (group 2). The transient multiphysics interaction simulation method was applied to elucidate the differences in biomechanical and acoustic parameters between the two groups. The results revealed that the blood flow pattern at the TS and sigmoid sinus junction was significantly changed depending on the stenosis position. Preoperative patients had increased blood flow in the TSS region and TSS downstream where the blood flow impacted the vessel wall. In group 1, the postoperative blood flow pattern, average wall pressure, vessel wall vibration, and sound pressure level of the three patients were comparable to the preoperative state. However, the postoperative blood flow velocity decreased in group 2. The postoperative average wall pressure, vessel wall vibration, and sound pressure level of the three patients were significantly improved compared with the preoperative state. Intravascular intervention therapy should be considered for patients with moderate TSS caused by arachnoid granulations in the middle and proximal involvement segment of the TS. TSS might not be considered the cause of VPT symptoms in patients with moderate TSS caused by arachnoid granulation in the middle segment of the TS.

Although coronavirus disease 2019 (COVID-19) primarily affects the respiratory system, this disease can affect multiple systems, including the musculoskeletal system. However, studies regarding the effect of COVID-19 on musculoskeletal system are limited. This study analyzed the bone mineral density (BMD) and body composition of 33 patients with COVID-19 using their chest CT scans at admission, discharge, and one-year follow-up. Among the patients, 2 were asymptomatic, 8 had mild symptoms, 19 had ordinary symptoms, and 4 had severe symptoms, and no critical patients were included. The mean length of hospital stay was (29.5±9.6) days, and the mean duration to follow-up was (423.0±53.6) days. The study found no significant changes in BMD of segmental or total thoracic vertebrae at admission, discharge, and one-year follow-up. No significant changes were observed in the subcutaneous adipose tissue (SAT) area, visceral adipose tissue (VAT) area, and total adipose tissue (TAT) of the mid-slice of the T12~L1 intervertebral disc. However, the asymptomatic and mild group had a higher average BMD of the T1~T12 than that of the common and severe group at admission and one-year follow-up. The common and severe group had higher VAT and TAT area than those of the asymptomatic and mild group at admission and one-year follow-up. This study provides valuable insights into the effects of COVID-19 on the musculoskeletal system and suggests that COVID-19 does not significantly affect thoracic BMD and abdominal adipose tissue after one year of infection.

Objective: To observe the CT and MRI findings in newly diagnosed patients with IgG4-related sclerosing cholangitis (IgG4-SC) and explore their correlations with serum IgG4 and IgG levels. Methods: The clinical, laboratory, and imaging data of 50 newly diagnosed IgG4-SC patients were retrospectively summarized. The type of lesions, shape of lumen stenosis, degree of dilatation of the diseased bile ducts on MRCP, characteristics and enhancement patterns of the thickened bile duct walls, and the number of other coexisting IgG4-RDs on enhanced MRI and CT were observed. Subsequently, the correlations of the patients' baseline serum IgG4 and IgG levels with the severity of bile duct lesions and the number of other coexisting IgG4-RDs were analyzed. Results: Forty-one patients underwent MRCP examinations, and the following types of IgG4-SC were identified: type Ⅰ in 28 cases, type Ⅱa in 11, type Ⅲ in 1, and type Ⅳ in 1. Extrahepatic bile duct stenosis was funnel-shaped in 37 cases and truncated in 4 cases. Moreover, all the stenotic segments were long (≥1.0 cm) and one diverticulum-like outpouching was seen in the pancreatic segment stenosis. Upstream bile ducts of the stenosis showed dilatation in 37 cases, while the other 4 cases did not show this. Contrast-enhanced MRI and CT examinations showed continuous thickening of the extrahepatic bile duct walls in 42 cases, and diffuse thickening of the intrahepatic bile duct walls was simultaneously observed in 15 cases among them. The thickness of the bile duct walls was uniformly concentric. Meanwhile, other accompanying IgG4-RDs included AIP in 50 cases, kidney involvement in 19, salivary gland involvement in 7, retroperitoneal fibrosis in 5, liver involvement in 4, lung involvement in 4, prostate involvement in 2, sclerosing mediastinitis in 2, thickened gallbladder wall (without stones) in 20, and enlarged upper abdominal lymph nodes in 15 cases. Moreover, higher baseline serum IgG4 and IgG levels were positively correlated with the number of other coexisting IgG4-RDs, but not with the bile duct wall thickness and stenotic segment length. Conclusions: Localized stenosis of the bile ducts with dilatation or non-dilation of the upstream bile ducts, as well as diffuse thickening of the bile duct walls, are the MRI and CT features of newly diagnosed patients with IgG4-SC. Furthermore, higher baseline serum IgG4 and IgG levels are not related to the severity of the diseased bile ducts but are related to the number of other coexisting IgG4-RDs.

Abstract Accurate vestibule segmentation for CT images is of great significance for the clinical diagnosis of congenital ear malformations and cochlear implant. However, it is still a challenging task due to extremely small size and irregular shape of vestibule. Here, a vestibule segmentation network for CT images is proposed under the basic encoder‐decoder framework. Firstly, a residual block based on channel attention mechanism, named Res‐CA block, is designed to guide the network to enhance the important features for the segmentation tasks while suppressing the irrelevant ones. And then, a global context‐aware pyramid feature extraction (GCPFE) module is proposed to capture multi‐receptive‐field global context information. Finally, active contour with elastic (ACE) loss function is adopted to guide network learning more detailed information of the boundary. Furthermore, deep supervision (DS) mechanism is employed to locate the boundaries finely, improving the robustness of the network. The experiments are conducted on the self‐established VestibuleDataset and UHRCT‐Dataset, as well as publicly available retinal dataset, namely DRIVE, to comprehensively verify the robustness and generalization capability of the proposed segmentation network. The experimental results show that the proposed network can achieve a superior performance.

Tinnitus is associated with abnormal functional connectivity of multiple regions of the brain. However, previous analytic methods have disregarded information on the direction of functional connectivity, leading to only a moderate efficacy of pretreatment planning. We hypothesized that the pattern of directional functional connectivity can provide key information on treatment outcomes. Sixty-four participants were enrolled in this study: eighteen patients with tinnitus were categorized into the effective group, twenty-two patients into the ineffective group, and twenty-four healthy participants into the healthy control group. We acquired resting-state functional magnetic resonance images prior to sound therapy and constructed an effective connectivity network of the three groups using an artificial bee colony algorithm and transfer entropy. The key feature of patients with tinnitus was the significantly increased signal output of the sensory network, including the auditory, visual, and somatosensory networks, and parts of the motor network. This provided critical insights into the gain theory of tinnitus development. The altered pattern of functional information orchestration, represented by a higher degree of hypervigilance-driven attention and enhanced multisensory integration, may explain poor clinical outcomes. The activated gating function of the thalamus is one of the key factors for a good prognosis in tinnitus treatment. We developed a novel method for analyzing effective connectivity, facilitating an understanding of the tinnitus mechanism and treatment outcome expectation based on the direction of information flow.

Objective: To summarize the imaging features of acute necrotic collections (ANC), a local complication of acute necrotizing pancreatitis (ANP), and to explore the factors affecting the prognosis of patients with ANC. Methods: The clinical and imaging data of 31 patients with ANP were analyzed retrospectively. Characteristics of ANC on computed tomography (CT) and magnetic resonance imaging (MRI) were analyzed as well. Based on the follow-up outcomes, patients were divided into the absorption group and the walled-off necrosis (WON) group; a chi-square test was used to compare the two. Results: Plain CT revealed patchy, uneven, low-density shadows in 31 cases of ANC (focal, oval, and iso-density and low-density mixed shadows:23 cases; fatty low-density shadows: 22 cases). Plain MRI revealed mixed low-signal intensities on T1-weighted imaging and mixed high-signal intensities on T2-weighted imaging in 19 cases of ANC; low-signal fragments were seen on Fat suppressed T2-weighted imaging in some of these cases. ANC was complicated with local infection and hemorrhage in 3 (9.7%) and 12 (38.7%) cases, respectively. The necrotic tissues did not show any enhancement, but the surrounding tissues appeared patchy or linear-enhancing changes with varying degrees on enhanced scans. Follow-up examination (median: 137 days) revealed that ANC was completely absorbed in 12 cases (38.7%) and had developed into WON in 19 cases (61.3%). The absorption and WON groups differed significantly in terms of necrosis involving the pancreas, affected locations of the pancreas, necrotic volumes, and the modified CT severity index scores. Conclusion: On CT and MRI, ANC appears as uneven liquid densities and heterogeneous signal intensities, respectively. The necrotic tissue itself has no enhancement, but its surrounding tissue presents with different degrees of enhancing changes on enhanced scanning. Follow-up findings reveal that ANC can completely dissipate or progress to WON, which is related to several imaging factors.

Objectives: The degree of endolymphatic hydrops in Meniere's disease may be related to hearing loss. However, the results of prior studies have been inconsistent. We aimed to investigate the relationship between endolymphatic hydrops and hearing loss characteristics in Meniere’s disease. Methods: This study included 54 patients (62 ears) with Meniere’s disease. Patients underwent three-dimensional real inversion recovery sequences for magnetic resonance imaging and pure-tone audiometry. Endolymphatic hydrops were assessed according to Gurkov’s criteria (2011). Correlations between different degrees of endolymphatic hydrops and pure-tone audiometry, as well as staging, were analysed. Results: Pure tone audiometry and staging were higher for vestibular endolymphatic hydrops complicated by cochlear ones than isolated cochlear or vestibular hydrops (both p 0.05). The degree of hydrops in the middle turn was correlated with the mid-frequency hearing threshold (p

Key points The radiology residents at all levels in China were systematically landscaped. 68.6% of the 3666 residents reported satisfaction with the residency training. Radiation protection was significantly associated with residency satisfaction. Satisfaction significantly impacts radiology residents’ well-being, professional identity and self-reported competency. The findings provide new insights into sustaining and improving the radiology residency.

Abstract Purpose To retrospectively assess the accuracy of magnetic resonance imaging (MRI) in defining dentate line in anal fistula. Materials and methods Seventy patients with anal fistulas were assessed by dynamic contrast-enhanced MRI. The distance from the dentate line to the anal verge for all patients was measured by MRI. To mitigate interference, 35 patients with anal fistulas whose internal openings were located on the dentate line were excluded from this study. Two observers independently judged the positional relationship between the internal opening and the MRI-defined dentate line, and compared with the results observed by surgeon to assess the accuracy. Results The distance between the MRI-defined dentate line and the anal verge depended on the location of the internal opening and the morphology of the anal canal mucosa. The distance based on the location the internal opening and the morphology of the anal canal mucosa was 18.2 ± 8.1 mm and 20.0 ± 5.3 mm on oblique coronal T2WI, respectively. Compared with the results observed by the surgeon, the accuracy of evaluating the positional relationship between the internal opening and the dentate line from the morphology of the anal canal mucosa on MRI exceeded 89.9%. Taking 18.2–20.0 mm as the distance between the dentate line and the anal verge on the MRI image, the accuracy of evaluating the relationship between the position of the internal opening and the dentate line was over 85.7%. Considering both the dentate line and the anal canal mucosa, the accuracy of evaluating the relationship between the internal opening and the dentate line was over 91.5%. The results of MRI-defined dentate line were in good agreement with the results of intraoperative surgeon evaluation, and the κ values were 0.70, 0.63, and 0.78, respectively. Conclusion MRI has high accuracy in defining the dentate line in anal fistulas.

Abstract Background The aim of this study was to investigate the ability of a pixel-to-pixel generative adversarial network (GAN) to remove motion artefacts in coronary CT angiography (CCTA) images. Methods Ninety-seven patients who underwent single-cardiac-cycle multiphase CCTA were retrospectively included in the study, and raw CCTA images and SnapShot Freeze (SSF) CCTA images were acquired. The right coronary artery (RCA) was investigated because its motion artefacts are the most prominent among the artefacts of all coronary arteries. The acquired data were divided into a training dataset of 40 patients, a verification dataset of 30 patients and a test dataset of 27 patients. A pixel-to-pixel GAN was trained to generate improved CCTA images from the raw CCTA imaging data using SSF CCTA images as targets. The GAN’s ability to remove motion artefacts was evaluated by the structural similarity (SSIM), Dice similarity coefficient (DSC) and circularity index. Furthermore, the image quality was visually assessed by two radiologists. Results The circularity was significantly higher for the GAN-generated images than for the raw images of the RCA (0.82 ± 0.07 vs. 0.74 ± 0.11, p

Wheat straw burial has great potential to sustain rice production under alternate wetting and drying (AWD) irrigation. A field experiment was conducted with three wheat straw burial treatments, including without straw burial (NSB), with light straw burial of 300 kg/hm2 (LSB) and dense straw burial of 800 kg/hm2 (DSB), as well as three AWD regimes: alternate wetting/moderate drying (AWMD), alternate wetting/severe drying (AWSD) and alternate wetting/critical drying (AWCD). The rice growth and grain quality were higher in LSB and NSB than those in NSB under the same AWD regime. The AWMD × DSB treatment resulted in the highest yield, brown rice rate, milled rice rate, amylose content and protein content. Conversely, the AWCD × NSB treatment led to the lowest yield, brown rice rate, milled rice rate, amylose content and protein content. The active absorption area and nitrate reductase activity of roots were higher in the AWMD × DSB treatment than those in the AWCD × NSB treatment, as the former increased organic carbon and nitrogen contents in the rhizosphere, whereas the latter reduced their availability. Total soluble protein content and glutamine synthetase activity were greater in the AWMD × DSB treatment than those in the AWCD × NSB treatment. The activities of superoxide dismutase and catalase were higher in the AWMD × DSB treatment compared with the AWCD × NSB treatment, leading to the amelioration of oxidative cell injury, as shown by a lower malonaldehyde level. This study suggested that farmers should implement AWMD irrigation after leaving the straw residues in the field, followed by deep tillage to improve soil quality and mitigate the drought stress cycles of AWD. This approach can improve rice growth and grain quality and alleviate the problems of disposal of straw residues and water scarcity for sustainable rice production.

Aridity and soil erosion are two bottlenecks restricting the sustainable development of the Loess Plateau and are also fundamental reasons for the ecological fragility of the region. A gravity subsurface hole irrigation system was proposed to regulate rainfall–runoff, achieve rainwater stylization, and reduce soil erosion. Based on HYDRUS-2D/3D, a mathematical model of soil water movement under gravity subsurface hole irrigation was created. Thirty-five scenarios were designed to analyze five cumulative infiltration volumes (I) and wetting front migration distance (W), and changes under different combinations of saturated hydraulic conductivity (Ks), infiltrating hole diameter (D), infiltrating pipe depth (B), matric potential (Ψm), and infiltration time (T). The results indicated that when Ks, D, B, and T increased, I also increased, while Ψm increased and I decreased. In addition, when I and Ψm increase, W increases. However, when D and B increase, W decreases. Ks promotes W in a vertical downward direction but inhibits W in the vertically upward and horizontal directions. The simulation results established the I estimation model and the W estimation model (power function continuous multiplication form). There was acceptable uniformity among the predicted and measured values, and its reliability was verified experimentally. HIGHLIGHTS A new technology of rainwater harvesting and irrigation saving for arid and semi-arid areas was designed.; A soil water transport model for designers and irrigation users was established.; The model was validated by experimental data, and the prediction effect was good.;

Abstract Background Given the increasing number of people suffering from tinnitus, the accurate categorization of patients with actionable reports is attractive in assisting clinical decision making. However, this process requires experienced physicians and significant human labor. Natural language processing (NLP) has shown great potential in big data analytics of medical texts; yet, its application to domain-specific analysis of radiology reports is limited. Objective The aim of this study is to propose a novel approach in classifying actionable radiology reports of tinnitus patients using bidirectional encoder representations from transformer BERT-based models and evaluate the benefits of in domain pre-training (IDPT) along with a sequence adaptation strategy. Methods A total of 5864 temporal bone computed tomography(CT) reports are labeled by two experienced radiologists as follows: (1) normal findings without notable lesions; (2) notable lesions but uncorrelated to tinnitus; and (3) at least one lesion considered as potential cause of tinnitus. We then constructed a framework consisting of deep learning (DL) neural networks and self-supervised BERT models. A tinnitus domain-specific corpus is used to pre-train the BERT model to further improve its embedding weights. In addition, we conducted an experiment to evaluate multiple groups of max sequence length settings in BERT to reduce the excessive quantity of calculations. After a comprehensive comparison of all metrics, we determined the most promising approach through the performance comparison of F1-scores and AUC values. Results In the first experiment, the BERT finetune model achieved a more promising result (AUC-0.868, F1-0.760) compared with that of the Word2Vec-based models(AUC-0.767, F1-0.733) on validation data. In the second experiment, the BERT in-domain pre-training model (AUC-0.948, F1-0.841) performed significantly better than the BERT based model(AUC-0.868, F1-0.760). Additionally, in the variants of BERT fine-tuning models, Mengzi achieved the highest AUC of 0.878 (F1-0.764). Finally, we found that the BERT max-sequence-length of 128 tokens achieved an AUC of 0.866 (F1-0.736), which is almost equal to the BERT max-sequence-length of 512 tokens (AUC-0.868,F1-0.760). Conclusion In conclusion, we developed a reliable BERT-based framework for tinnitus diagnosis from Chinese radiology reports, along with a sequence adaptation strategy to reduce computational resources while maintaining accuracy. The findings could provide a reference for NLP development in Chinese radiology reports.

IntroductionHigh myopia (HM) is a public health issue that can lead to severe visual impairment. Previous studies have exhibited widespread white matter (WM) integrity damage in HM patients. However, how these WM damages are topologically related, and the network-level structural disruptions underlying HM has not been fully defined. We aimed to assess the alterations of brain WM structural networks in HM patients using diffusion kurtosis imaging (DKI) and tractography in the present study.MethodsIndividual whole-brain and ROI-level WM networks were constructed using DKI tractography in 30 HM patients and 33 healthy controls. Graph theory analysis was then applied to explore the altered global and regional network topological properties. Pearson correlations between regional properties and disease duration in the HM group were also assessed.ResultsFor global topology, although both groups showed a small-world network organization, HM patients exhibited significant decreased local efficiency and clustering coefficient compared with controls. For regional topology, HM patients and controls showed highly similar hub distributions, except for three additional hub regions in HM patients including left insula, anterior cingulate and paracingulate gyri (ACG), and median cingulate and paracingulate gyri (DCG). In addition, HM patients showed significantly altered nodal betweenness centrality (BC) mainly in the bilateral inferior occipital gyrus (IOG), left superior occipital gyrus (SOG), caudate nucleus, rolandic operculum and right putamen, pallidum, and gyrus rectus compared with controls. Intriguingly, the nodal BC of left IOG was negatively correlated with disease duration in HM patients.DiscussionOur findings suggest that HM exhibited alterations in WM structural networks as indicated by decreased local specialization. This study may advance the current understanding of the pathophysiological mechanisms underlying HM.

Abstract Background Bulimia nervosa is a recurrent eating disorder with uncertain pathogenesis. Recently, there has been growing interest in using neuroimaging techniques to explore brain structural and functional alterations in bulimia nervosa, but the findings of previous studies have a great number of inconsistencies. Methods Here, we collected anatomical and resting‐state functional magnetic resonance imaging data from 43 bulimia nervosa patients and 34 matched healthy controls (HCs). We applied a surface‐based morphology analysis to explore brain cortical morphology differences and a novel surface‐based functional connectivity (FC) analysis to investigate functional abnormalities. Principal component analysis was performed to analyze the behavioral data of the participants. We further analyzed the relationships between abnormalities in cortical characteristics or FC and clinical features. Results We observed increased greater sulcal depth in the right superior temporal gyrus (STG) and the right medial orbitofrontal cortex (mOFC) in bulimia nervosa patients than in the HCs. Additionally, the patients exhibited increased FC between the right STG and right ventral tegmental area but decreased function between the right mOFC and right putamen, which was significantly negatively correlated with the first principal component reflecting the severity of bulimia nervosa symptom. Conclusions Our findings provide evidence of neuroanatomical and functional abnormalities in bulimia nervosa patients. Moreover, the FC between the right mOFC and right putamen was associated with symptom severity of bulimia nervosa, which may be a neural marker and involved in the neuropathological mechanism of bulimia nervosa.

BackgroundIt is well known that the occurrence and development of ovarian cancer are closely related to the patient’s weight and various endocrine factors in the body.AimMendelian randomization (MR) was used to analyze the bidirectional relationship between insulin related characteristics and ovarian cancer.MethodsThe data on insulin related characteristics are from up to 5567 diabetes free patients from 10 studies, mainly including fasting insulin level, insulin secretion rate, peak insulin response, etc. For ovarian cancer, UK Biobank data just updated in 2021 was selected, of which the relevant gene data was from 199741 Europeans. Mendelian randomization method was selected, with inverse variance weighting (IVW) as the main estimation, while MR Pleiotropy, MR Egger, weighted median and other methods were used to detect the heterogeneity of data and whether there was multi validity affecting conclusions.ResultsAmong all insulin related indicators (fasting insulin level, insulin secretion rate, peak insulin response), the insulin secretion rate was selected to have a causal relationship with the occurrence of ovarian cancer (IVW, P < 0.05), that is, the risk of ovarian cancer increased with the decrease of insulin secretion rate. At the same time, we tested the heterogeneity and polymorphism of this indicator, and the results were non-existent, which ensured the accuracy of the analysis results. Reverse causal analysis showed that there was no causal effect between the two (P>0.05).ConclusionThe impairment of the insulin secretion rate has a causal effect on the risk of ovarian cancer, which was confirmed by Mendel randomization. This suggests that the human glucose metabolism cycle represented by insulin secretion plays an important role in the pathogenesis of ovarian cancer, which provides a new idea for preventing the release of ovarian cancer.

Introduction Multi-modality medical imaging study, especially brain MRI, greatly facilitates the research on subclinical brain disease. However, there is still a lack of such studies with a wider age span of participants. The Multi-modality MEdical imaging sTudy bAsed on KaiLuan Study (META-KLS) was designed to address this issue with a large sample size population.Methods and analysis We aim to enrol at least 1000 subjects in META-KLS. All the participants without contraindications will perform multi-modality medical imaging, including brain MRI, retinal fundus photograph, fundus optical coherence tomography (OCT) and ultrasonography of the internal carotid artery (ICA) every 2–4 years. The acquired medical imaging will be further processed with a standardised and validated workflow. The clinical data at baseline and follow-up will be collected from the KaiLuan Study. The associations between multiple risk factors and subclinical brain disease are able to be fully investigated. Researches based on META-KLS will provide a series of state-of-the-art evidence for the prevention of neurological diseases and common chronic diseases.Ethics and dissemination The Kailuan Study and META-KLS have been approved by the Medical Ethics Committee of Kailuan General Hospital (IRB number: 2008 No. 1 and 2021002, respectively). Written informed consent will be acquired from each participant. Results are expected to be published in professional peer-reviewed journals beginning in 2023.Trial registration number NCT05453877.

IntroductionThere is a growing interest in exploring brain-heart interactions. However, few studies have investigated the brain-heart interactions in healthy populations, especially in healthy young adults. The aim of this study was to explore the association between cardiovascular and spontaneous brain activities during dobutamine infusion in healthy young adults.MethodsForty-eight right-handed healthy participants (43 males and 5 females, range: 22–34 years) underwent vital signs monitoring, cognitive function assessment and brain MRI scans. Cardiovascular function was evaluated using blood pressure and heart rate, while two resting-state functional magnetic resonance imaging (rs-fMRI) methods—regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF)—were used together to reflect the local neural activity of the brain. Logistic regression was used to model the association between brain and heart.ResultsResults showed that blood pressure and heart rate significantly increased after dobutamine infusion, and the performance in brain functional activity was the decrease in ReHo in the left gyrus rectus and in ALFF in the left frontal superior orbital. The results of logistic regression showed that the difference of diastolic blood pressure (DBP) had significant positive relationship with the degree of change of ReHo, while the difference of systolic blood pressure (SBP) had significant negative impact on the degree of change in ALFF.DiscussionThese findings suggest that the brain-heart interactions exist in healthy young adults under acute cardiovascular alterations, and more attention should be paid to blood pressure changes in young adults and assessment of frontal lobe function to provide them with more effective health protection management.

Abstract Background To investigate the influence of artificial intelligence (AI) based on deep learning on the diagnostic performance and consistency of inexperienced cardiovascular radiologists. Methods We enrolled 196 patents who had undergone both coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) within 6 months. Four readers with less cardiovascular experience (Reader 1–Reader 4) and two cardiovascular radiologists (level II, Reader 5 and Reader 6) evaluated all images for ≥ 50% coronary artery stenosis, with ICA as the gold standard. Reader 3 and Reader 4 interpreted with AI system assistance, and the other four readers interpreted without the AI system. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (area under the receiver operating characteristic curve (AUC)) of the six readers were calculated at the patient and vessel levels. Additionally, we evaluated the interobserver consistency between Reader 1 and Reader 2, Reader 3 and Reader 4, and Reader 5 and Reader 6. Results The AI system had 94% and 78% sensitivity at the patient and vessel levels, respectively, which were higher than that of Reader 5 and Reader 6. AI-assisted Reader 3 and Reader 4 had higher sensitivity (range + 7.2–+ 16.6% and + 5.9–+ 16.1%, respectively) and NPVs (range + 3.7–+ 13.4% and + 2.7–+ 4.2%, respectively) than Reader 1 and Reader 2 without AI. Good interobserver consistency was found between Reader 3 and Reader 4 in interpreting ≥ 50% stenosis (Kappa value = 0.75 and 0.80 at the patient and vessel levels, respectively). Only Reader 1 and Reader 2 showed poor interobserver consistency (Kappa value = 0.25 and 0.37). Reader 5 and Reader 6 showed moderate agreement (Kappa value = 0.55 and 0.61). Conclusions Our study showed that using AI could effectively increase the sensitivity of inexperienced readers and significantly improve the consistency of coronary stenosis diagnosis via CCTA. Trial registration Clinical trial registration number: ChiCTR1900021867. Name of registry: Diagnostic performance of artificial intelligence-assisted coronary computed tomography angiography for the assessment of coronary atherosclerotic stenosis.

ObjectivesTo assess the lateralization of cerebral blood flow (CBF) in the auditory cortex of idiopathic tinnitus patients and healthy controls (HCs) using 3D pseudocontinuous arterial spin labeling (pcASL).MethodsThirty-six patients with idiopathic tinnitus and 43 sex- and age-matched HCs underwent 3D-pcASL scanning using a 3.0 T MRI system. For both groups, region of interest analysis was performed on the primary auditory cortex (PAC), auditory associative cortex (AAC), and secondary auditory cortex (SAC). The clinical data of all subjects were analyzed.ResultsIn both tinnitus patients and HCs, CBF of the left PAC was significantly higher than that of the right (HCs: P = 0.02; patients: P = 0.043), but CBF of the right AAC and SAC was significantly higher than that of the left (AAC: HCs, P < 0.001; patients: P < 0.001. SAC: HCs, P < 0.001; patients: P = 0.001). Compared with HCs, tinnitus patients exhibited significantly higher CBF in the bilateral PAC (right: P = 0.008; left: P = 0.022). CBF in the left PAC was positively correlated with tinnitus severity (r = 0.399, P = 0.016).ConclusionThis study confirms the asymmetry of the auditory cortex and investigates the underlying neuropathology of idiopathic tinnitus in terms of CBF.

Natural abundance of the stable isotope (δ13C and δ15N) in plants is widely used to indicate water use efficiency (WUE). However, soil water and texture properties may affect this relationship, which remains largely elusive. Therefore, the purpose of this study was to evaluate δ13C as affected by different combinations of alternate wetting and drying irrigation (AWD) with varied soil clay contents in different organs and whole plant and assess the feasibility of using δ13C and δ15N as a physiological indicator of whole-plant water use efficiency (WUEwhole-plant). Three AWD regimes, I100 (30 mm flooded when soil reached 100% saturation), I90 (30 mm flooded when reached 90% saturation) and I70 (30 mm flooded when reached 70% saturation) and three soil clay contents, 40% (S40), 50% (S50), and 60% (S60), were included. Observed variations in WUEwhole-plant did not conform to theoretical expectations of the organs δ13C (δ13Corgans) of plant biomass based on pooled data from all treatments. However, a positive relationship between δ13Cleaf and WUEET (dry biomass/evapotranspiration) was observed under I90 regime, whereas there were no significant relationships between δ13Corgans and WUEET under I100 or I70 regimes. Under I100, weak relationships between δ13Corgans and WUEET could be explained by (i) variation in C allocation patterns under different clay content, and (ii) relatively higher rate of panicle water loss, which was independent of stomatal regulation and photosynthesis. Under I70, weak relationships between δ13Corgans and WUEET could be ascribed to (i) bigger cracks induced by water-limited irrigation regime and high clay content soil, and (ii) damage caused by severe drought. In addition, a negative relationship was observed between WUEwhole-plant and shoot δ15N (δ15Nshoot) across the three irrigation treatments, indicating that WUEwhole-plant is tightly associated with N metabolism and N isotope discrimination in rice. Therefore, δ13C should be used cautiously as an indicator of rice WUEwhole-plant at different AWD regimes with high clay content, whereas δ15N could be considered an effective indicator of WUEwhole-plant.

ObjectiveThe aim of this study was to determine whether the visual pathway is affected by thyroid-associated ophthalmopathy (TAO) before the development of dysthyroid optic neuropathy (DON) with diffusion tensor imaging (DTI).Materials and methodsFifty-seven TAO patients (22 mild, 35 moderate-severe TAO) and 30 healthy controls (HCs) were included. The DTI parameters of the lateral geniculate (LG) and optic radiation (OR) were measured. A full ophthalmic examination such as intraocular pressure, exophthalmos, and visual acuity was performed. Clinical activity scores (CAS) were also calculated. One-way ANOVA and Pearson's correlation were carried out. A binary logistic regression was used to identify variables that can diagnose TAO.ResultsModerate-severe TAO patients showed significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD) than HCs for both LG and OR (p < 0.05). FA of OR was negatively correlated with CAS and intraocular pressure (p < 0.05). Multivariate analysis showed that FA of LG and FA of OR were a significant predictor for the diagnosis TAO.ConclusionDiffusion tensor imaging parameters of the visual pathway were significantly altered in moderate-severe TAO patients. The FA of LG, in particular, can be used as a sensitive imaging biomarker for assessing subclinical visual pathway damage in TAO.

Purpose: Ocular blood flow (OBF) is an important risk factor for incidence, prevalence and progression of some ocular disorders. To date, there are very limited therapeutic options to increase OBF. This study investigated the effect of dobutamine on OBF of heathy adults using 3D pseudocontinuous arterial spin labelling (3D-pcASL), and explored the risk factors associated with OBF.Methods: Forty-three healthy participants (86 eyes) were given an intravenous injection of dobutamine. We measured OBF using 3D-pcASL with a 3.0T- MRI scanner, OBF values were independently obtained by two doctors from the OBF map. We also collected physiological parameters using a vital signs monitor. The OBF and physiological parameters in the in the period before and after dobutamine injection states were obtained.Results: OBF increased significantly after dobutamine injection using paired t test method (from 22.43 ± 9.87 to 47.73 ± 14.02 ml/min/100g, p < 0.001). Age, heart rate and systolic blood pressure were the main risk factors affecting OBF using logistic regression analysis (all p values < 0.05).Conclusion: To the best of our knowledge, this is the first study observing the effect of dobutamine on OBF. Our findings indicated that intravenously injected dobutamine increased OBF, making it a possible option to counteract ocular vascular ischaemia in the future.

BackgroundMedical imaging is critical in clinical practice, and high value radiological reports can positively assist clinicians. However, there is a lack of methods for determining the value of reports.ObjectiveThe purpose of this study was to establish an ensemble learning classification model using natural language processing (NLP) applied to the Chinese free text of radiological reports to determine their value for liver lesion detection in patients with colorectal cancer (CRC).MethodsRadiological reports of upper abdominal computed tomography (CT) and magnetic resonance imaging (MRI) were divided into five categories according to the results of liver lesion detection in patients with CRC. The NLP methods including word segmentation, stop word removal, and n-gram language model establishment were applied for each dataset. Then, a word-bag model was built, high-frequency words were selected as features, and an ensemble learning classification model was constructed. Several machine learning methods were applied, including logistic regression (LR), random forest (RF), and so on. We compared the accuracy between priori choosing pertinent word strings and our machine language methodologies.ResultsThe dataset of 2790 patients included CT without contrast (10.2%), CT with/without contrast (73.3%), MRI without contrast (1.8%), and MRI with/without contrast (14.6%). The ensemble learning classification model determined the value of reports effectively, reaching 95.91% in the CT with/without contrast dataset using XGBoost. The logistic regression, random forest, and support vector machine also achieved good classification accuracy, reaching 95.89%, 95.04%, and 95.00% respectively. The results of XGBoost were visualized using a confusion matrix. The numbers of errors in categories I, II and V were very small. ELI5 was used to select important words for each category. Words such as “no abnormality”, “suggest”, “fatty liver”, and “transfer” showed a relatively large degree of positive correlation with classification accuracy. The accuracy based on string pattern search method model was lower than that of machine learning.ConclusionsThe learning classification model based on NLP was an effective tool for determining the value of radiological reports focused on liver lesions. The study made it possible to analyze the value of medical imaging examinations on a large scale.

ObjectivesTo evaluate the potential improvement of prediction performance of a proposed double branch multimodality-contribution-aware TripNet (MCAT) in microvascular invasion (MVI) of hepatocellular carcinoma (HCC) based on a small sample.MethodsIn this retrospective study, 121 HCCs from 103 consecutive patients were included, with 44 MVI positive and 77 MVI negative, respectively. A MCAT model aiming to improve the accuracy of deep neural network and alleviate the negative effect of small sample size was proposed and the improvement of MCAT model was verified among comparisons between MCAT and other used deep neural networks including 2DCNN (two-dimentional convolutional neural network), ResNet (residual neural network) and SENet (squeeze-and-excitation network), respectively.ResultsThrough validation, the AUC value of MCAT is significantly higher than 2DCNN based on CT, MRI, and both imaging (P < 0.001 for all). The AUC value of model with single branch pretraining based on small samples is significantly higher than model with end-to-end training in CT branch and double branch (0.62 vs 0.69, p=0.016, 0.65 vs 0.83, p=0.010, respectively). The AUC value of the double branch MCAT based on both CT and MRI imaging (0.83) was significantly higher than that of the CT branch MCAT (0.69) and MRI branch MCAT (0.73) (P < 0.001, P = 0.03, respectively), which was also significantly higher than common-used ReNet (0.67) and SENet (0.70) model (P < 0.001, P = 0.005, respectively).ConclusionA proposed Double branch MCAT model based on a small sample can improve the effectiveness in comparison to other deep neural networks or single branch MCAT model, providing a potential solution for scenarios such as small-sample deep learning and fusion of multiple imaging modalities.

ObjectiveTo quantitatively evaluate the bilateral diaphragmatic motion difference during forced breathing between chronic obstructive pulmonary disease (COPD) patients and healthy individuals using dynamic chest radiography technique.MethodsThis prospective study included the COPD patients (n: 96, f/m: 17/79, age: 66 ± 8 years old) and healthy individuals (n: 50, f/m: 42/8, age: 53 ± 5 years old) that underwent dynamic chest radiography with a flat panel X-ray detector system during forced breathing in a standing position. After analyzing the excursions, duration and velocity of diaphragmatic motion were automatically calculated using the postprocessing software. The parameters of diaphragmatic motion including excursion, duration, velocity, inhalation/exhalation times were assessed in all subjects for both diaphragms. The correlation between lung function parameters and diaphragmatic motion excursions were further evaluated.ResultsThe excursions of diaphragmatic motion in COPD patients were significantly decreased in COPD patients compared with healthy individuals during forced breathing (P < 0.05). The excursion in COPD patients was 35.93 ± 13.07 mm vs. 41.49 ± 12.07 mm in healthy individuals in the left diaphragm, and 32.05 ± 12.29 mm in COPD patients vs. 36.88 ± 10.96 mm in healthy individuals in the right diaphragm. The duration of diaphragmatic motion significantly decreased in COPD patients, compared with the healthy individuals (P < 0.05). The inhalation time in COPD patients was 2.03 ± 1.19 s vs. 2.53 ± 0.83 s in healthy individuals in the left diaphragm and 1.94 ± 1.32 s in COPD patients vs. 2.23 ± 1.21 s in healthy individuals in the right diaphragm. The exhalation time was 4.77 ± 1.32 s in COPD patients vs. 6.40 ± 2.73 s in healthy individuals in the left diaphragm and 4.94 ± 3.30 s in COPD patients vs. 6.72 ± 2.58 s in healthy individuals in the right diaphragm. The peak velocity of diaphragmatic motion showed no significant difference between COPD and healthy groups. The excursions of bilateral diaphragmatic motion showed moderate correlation with FEV1/FVC (r = 0.44, P < 0.001). Multi-linear regression analysis showed that the excursions of bilateral diaphragm are significantly associated with COPD occurrence (P < 0.05).ConclusionThe excursions and duration of diaphragmatic motion during forced breathing are significantly decreased in COPD patients, compared with healthy individuals. Our study showed that precise bilateral diaphragmatic motion activity can be evaluated by dynamic chest radiography.