Role of Body Mass Index, Waist-to-Height and Waist-to-Hip Ratio in Prediction of Nonalcoholic Fatty Liver Disease

Objective. To investigate the anthropometric indicators that can effectively predict the nonalcoholic fatty liver disease (NAFLD). Methods. The height, body weight, waist and hip circumference were measured, and body mass index (BMI), waist-to-height (WHtR) and waist-to-hip ratio (WHR) were calculated. M-H chi square test, logistic regression analysis, and receiver-operating characteristic (ROC) curve were employed for the analysis of risk factors. Patients or Materials. 490 patients were recruited, of whom 250 were diagnosed as NAFLD and 240 as non-NAFLD (control group). Results. Compared with the control group, the BMI, WHR, and WHtR were significantly higher in patients with NAFLD. Logistic regression analysis showed that BMI and WHR were effective prognostic factors of NAFLD. In addition, WHR plays a more important role in prediction of NAFLD by the area under curve. Conclusion. WHR is closely related to the occurrence of NAFLD. We assume that WHR is beneficial for the diagnosis NAFLD

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem of each dataset, as well as a limited investigation of diverse types of tumors, the resulting models are often limited to segmenting specific organs/tumors and ignore the semantics of anatomical structures, nor can they be extended to novel domains. To address these issues, we propose the CLIP-Driven Universal Model, which incorporates text embedding learned from Contrastive Language-Image Pre-training (CLIP) to segmentation models. This CLIP-based label encoding captures anatomical relationships, enabling the model to learn a structured feature embedding and segment 25 organs and 6 types of tumors. The proposed model is developed from an assembly of 14 datasets, using a total of 3,410 CT scans for training and then evaluated on 6,162 external CT scans from 3 additional datasets. We rank first on the Medical Segmentation Decathlon (MSD) public leaderboard and achieve state-of-the-art results on Beyond The Cranial Vault (BTCV). Additionally, the Universal Model is computationally more efficient (6x faster) compared with dataset-specific models, generalized better to CT scans from varying sites, and shows stronger transfer learning performance on novel tasks.Comment: Rank first in Medical Segmentation Decathlon (MSD) Competitio

Differential evolution with two-level parameter adaptation

The performance of differential evolution (DE) largely depends on its mutation strategy and control parameters. In this paper, we propose an adaptive DE (ADE) algorithm with a new mutation strategy DE/lbest/1 and a two-level adaptive parameter control scheme. The DE/lbest/1 strategy is a variant of the greedy DE/best/1 strategy. However, the population is mutated under the guide of multiple locally best individuals in DE/lbest/1 instead of one globally best individual in DE/best/1. This strategy is beneficial to the balance between fast convergence and population diversity. The two-level adaptive parameter control scheme is implemented mainly in two steps. In the first step, the population-level parameters F p and CR p for the whole population are adaptively controlled according to the optimization states, namely, the exploration state and the exploitation state in each generation. These optimization states are estimated by measuring the population distribution. Then, the individual-level parameters F i and CR i for each individual are generated by adjusting the population-level parameters. The adjustment is based on considering the individual's fitness value and its distance from the globally best individual. This way, the parameters can be adapted to not only the overall state of the population but also the characteristics of different individuals. The performance of the proposed ADE is evaluated on a suite of benchmark functions. Experimental results show that ADE generally outperforms four state-of-the-art DE variants on different kinds of optimization problems. The effects of ADE components, parameter properties of ADE, search behavior of ADE, and parameter sensitivity of ADE are also studied. Finally, we investigate the capability of ADE for solving three real-world optimization problems

Clinical and Virological Characteristics of Chronic Hepatitis B Patients with Hepatic Steatosis

Abstract Objective: This study aimed to explore clinical and virological characteristics of chronic hepatitis B (CHB) patients with hepatic steatosis in order to provide a theoretical basis for the prevention and control of hepatic steatosis. Methods: A total of 360 CHB inpatients were recruited from Affiliated Dongnan Hospital of Xiamen University and divided into hepatic steatosis group and non-hepatic steatosis group. The body mass index (BMI), waist-to-hip ratio (WHR), fasting blood glucose (FBG), triglyceride (TG), total cholesterol (TC), aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), hepatitis B e antigen (HBeAg), hepatitis B virus DNA (HBV DNA) and hepatic histological changes were detected and compared between the two groups. The association of these factors with hepatic steatosis was evaluated in CHB patients. Results: BMI, FPG, TG, TC, GGT, AST and HBV DNA showed statistically significant differences between two groups (P<0.01). The patients with hepatic steatosis had markedly higher BMI, FBG, TG and TC than those without steatosis did. No significant differences were found in ALT and HBeAg between two groups (P>0.05). In male patients, there was marked difference in the WHR between two groups (P < 0.01), which was not found in female patients (P > 0.05). The severity of hepatic steatosis increased in patients with hepatic steatosis, compared to those without steatosis (P < 0. 01), but the severities of inflammation and fibrosis in the non-hepatic steatosis group were dramatically higher than those in the hepatic steatosis group (P < 0. 01). Conclusions: BMI, WHR, FBG, TG and TC appeared to be influencing factors of CHB combined with hepatic steatosis. Hepatic steatosis in CHB patients was closely related to changes in anthropometric indices and metabolic factors but not HBV. It is necessary to improve these factors to effectively prevent hepatic steatosis in CHB patients

Multi-parametric neuroimaging evaluation of cerebrotendinous xanthomatosis and its correlation with neuropsychological presentations

<p>Abstract</p> <p>Background</p> <p>Cerebrotendinous xanthomatosis (CTX) is a rare genetic disorder. Recent studies show that brain damage in CTX patients extends beyond the abnormalities observed on conventional magnetic resonance imaging (MRI). We studied the MRI and ^{99 m}Tc-ethyl cysteinate dimer single photon emission computed tomography (SPECT) findings of CTX patients and made a correlation with the neuropsychological presentations.</p> <p>Methods</p> <p>Diffusion tensor imaging (DTI) and 3D T1-weighted images of five CTX patients were compared with 15 age-matched controls. Voxel-based morphometry (VBM) was use to delineate gray matter (GM) and white matter (WM) volume loss. Fractional anisotropy (FA), mean diffusivity (MD), and eigenvalues derived from DTI were used to detect WM changes and correlate with neuropsychological results. SPECT functional studies were used to correlate with GM changes.</p> <p>Results</p> <p>Cognitive results showed that aside from moderate mental retardation, the patient group performed worse in all cognitive domains. Despite the extensive GM atrophy pattern, the cerebellum, peri-Sylvian regions and parietal-occipital regions were correlated with SPECT results. WM atrophy located in the peri-dentate and left cerebral peduncle areas corresponded with changes in diffusion measures, while axial and radial diffusivity suggested both demyelinating and axonal changes. Changes in FA and MD were preceded by VBM in the corpus callosum and corona radiata. Cognitive results correlated with FA changes.</p> <p>Conclusion</p> <p>In CTX, GM atrophy affected the perfusion patterns. Changes in WM included atrophy, and axonal changes with demyelination. Disconnection of major fiber tracts among different cortical regions may contribute to cognitive impairment.</p

Acute kidney disease following COVID-19 vaccination: a single-center retrospective study

BackgroundRare cases of de novo or relapsed kidney diseases associated with vaccination against coronavirus disease 2019 (COVID-19) have been increasingly reported. The aim of this study was to report the incidence, etiologies, and outcomes of acute kidney disease (AKD) following COVID-19 vaccination.MethodsThis retrospective study extracted cases from renal registry of a single medical center from 1 March 2021 to 30 April 2022, prior to the significant surge in cases of the Omicron variant of COVID-19 infection in Taiwan. Adult patients who developed AKD after COVID-19 vaccination were included. We utilized the Naranjo score as a causality assessment tool for adverse vaccination reactions and charts review by peer nephrologists to exclude other causes. The etiologies, characteristics, and outcomes of AKD were examined.ResultsTwenty-seven patients (aged 23 to 80 years) with AKD were identified from 1,897 vaccines (estimated rate of 13.6 per 1000 patient-years within the renal registry). A majority (77.8%) of vaccine received messenger RNA-based regimens. Their median (IQR) Naranjo score was 8 (6-9) points, while 14 of them (51.9%) had a definite probability (Naranjo score ≥ 9). The etiologies of AKD included glomerular disease (n = 16) consisting of seven IgA nephropathy, four anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN), three membranous glomerulonephritis, two minimal change diseases, and chronic kidney disease (CKD) with acute deterioration (n = 11). Extra-renal manifestations were found in four patients. Over a median (IQR) follow-up period of 42 (36.5–49.5) weeks, six patients progressed to end-stage kidney disease (ESKD).ConclusionBesides glomerulonephritis (GN), the occurrence of AKD following COVID-19 vaccination may be more concerning in high-risk CKD patients receiving multiple doses. Patients with the development of de novo AAN, concurrent extra-renal manifestations, or pre-existing moderate to severe CKD may exhibit poorer kidney prognosis

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE Xplore submission as part of WACV 202