Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma.

OBJECTIVES: To develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma. METHODS: Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without. RESULTS: PET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit. CONCLUSION: 18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best. CRITICAL RELEVANCE STATEMENT: 18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.

Predictors of dysphagia screening and pneumonia among patients with intracerebral haemorrhage in China: a cross-sectional hospital-based retrospective study.

OBJECTIVES: This study aimed to investigate factors associated with undergoing dysphagia screening (DS) and developing pneumonia, as well as the relationship between DS and pneumonia in patients with intracerebral haemorrhage (ICH). DESIGN: Our study was a cross-sectional hospital-based retrospective study. STUDY DESIGN AND SETTINGS: We derived data from the China Stroke Centre Alliance, a nationwide clinical registry of ICH from 1476 participating hospitals in mainland China. To identify predictors for pneumonia, multivariable logistic regression models were used to identify patient characteristics that were independently associated with DS and pneumonia. PARTICIPANTS: We included 31 546 patients in this study with patient characteristics, admission location, medical history, hospital characteristics and hospital grade from August 2015 to July 2019. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcomes were DS and pneumonia during acute hospitalisation. RESULTS: In total, 25 749 (81.6%) and 7257 (23.0%) patients with ICH underwent DS and developed pneumonia. Compared with patients without pneumonia, those who developed pneumonia were older and had severe strokes (Glasgow Coma Scale 9-13: 52.7% vs 26.9%). Multivariable analyses revealed that a higher pneumonia risk was associated with dysphagia (OR, 4.34; 95% CI, 4.02 to 4.68), heart failure (OR, 1.85; 95% CI, 1.24 to 2.77) and smoking (OR, 1.12; 95% CI, 1.12 to 0.20). DS was associated with lower odds of pneumonia (OR, 0.65; 95% CI, 0.44 to 0.95). CONCLUSION: Our findings further confirm that dysphagia is an independent risk factor for pneumonia; one-fifth of patients with ICH did not undergo DS. However, comprehensive dysphagia evaluation and effective management are crucial. Nursing processes ensure the collection of complete and accurate information during evaluation of patients. There is a need to increase the rate of DS in patients with ICH, especially those with severe stroke or older. Further, randomised controlled trials are warranted to determine the effectiveness of DS on clinical outcomes.

Identification of Parkinson's disease and multiple system atrophy using multimodal PET/MRI radiomics.

OBJECTIVES: To construct a machine learning model for differentiating Parkinson's disease (PD) and multiple system atrophy (MSA) by using multimodal PET/MRI radiomics and clinical characteristics. METHODS: One hundred and nineteen patients (81 with PD and 38 with MSA) underwent brain PET/CT and MRI to obtain metabolic images ([18F]FDG, [11C]CFT PET) and structural MRI (T1WI, T2WI, and T2-FLAIR). Image analysis included automatic segmentation on MRI, co-registration of PET images onto the corresponding MRI. Radiomics features were then extracted from the putamina and caudate nuclei and selected to construct predictive models. Moreover, based on PET/MRI radiomics and clinical characteristics, we developed a nomogram. Receiver operating characteristic (ROC) curves were performed to evaluate the performance of the models. Decision curve analysis (DCA) was employed to access the clinical usefulness of the models. RESULTS: The combined PET/MRI radiomics model of five sequences outperformed monomodal radiomics models alone. Further, PET/MRI radiomics-clinical combined model could perfectly distinguish PD from MSA (AUC = 0.993), which outperformed the clinical model (AUC = 0.923, p = 0.028) in training set, with no significant difference in test set (AUC = 0.860 vs 0.917, p = 0.390). However, no significant difference was found between PET/MRI radiomics-clinical model and PET/MRI radiomics model in training (AUC = 0.988, p = 0.276) and test sets (AUC = 0.860 vs 0.845, p = 0.632). DCA demonstrated the highest clinical benefit of PET/MRI radiomics-clinical model. CONCLUSIONS: Our study indicates that multimodal PET/MRI radiomics could achieve promising performance to differentiate between PD and MSA in clinics. CLINICAL RELEVANCE STATEMENT: This study developed an optimal radiomics signature and construct model to distinguish PD from MSA by multimodal PET/MRI imaging methods in clinics for parkinsonian syndromes, which achieved an excellent performance. KEY POINTS: •Multimodal PET/MRI radiomics from putamina and caudate nuclei increase the diagnostic efficiency for distinguishing PD from MSA. •The radiomics-based nomogram was developed to differentiate between PD and MSA. •Combining PET/MRI radiomics-clinical model achieved promising performance to identify PD and MSA.

Modulation of two-dimensional palladium nanozyme activity to enhance chemodynamic/photothermal combined therapy for melanoma.

Nanozymes are artificial enzymes that mimic natural enzyme-like activities and exhibit tremendous potential for tumor chemodynamic therapy. However, the development of novel nanozymes with superior catalytic activities for nanotheranostics remains a formidable challenge. Herein, we report a facile synthesis of monodisperse palladium nanosheets (Pd nanosheets) and their assembly on graphene oxide (GO) that enhances the catalytic activities of Pd nanoparticles. Simultaneously, the obtained nanocomposites (rGO-Pd) could be applied as a smart near-infrared (NIR) light-responsive nanotheranostic for near infrared imaging-guided chemodynamic/photothermal combined therapy. Notably, rGO-Pd exhibited high peroxidase mimicking activities, which could catalyze the conversion of intratumoral H2O2 to ˙OH. Impressively, the reactive oxygen species (ROS) generation of rGO-Pd was further remarkably enhanced by the endogenous acidity of the tumor microenvironment and the exogenous NIR light-responsive photothermal effect. These collective properties of the rGO-Pd nanozyme enabled it to be a ROS generation accelerator for photothermally enhanced tumor chemodynamic therapy. Thus, the as-developed rGO-Pd may represent a promising new type of high-performance nanozyme for multifunctional nanotheranostics toward cancer.

Displays of 18 F-FAPI PET/CT in Myocarditis With Variable Symptom Durations.

ABSTRACT: We report cardiac 18 F-FAPI PET/CT findings in 3 cases with myocarditis of varying duration (7 hours, 1 week, and 1 month). Myocarditis with varying symptom durations showed different 18 F-FAPI uptake, suggesting that the 18 F-FAPI PET/CT may be helpful in evaluating the extent of fibrosis caused by myocarditis. This information may assist in treatment decision-making for patients with myocarditis.

Assessment of rehabilitation following intracerebral hemorrhage in China: findings from the Chinese stroke center alliance.

OBJECTIVES: Evidence shows that rehabilitation is the most effective strategy to reduce the disability rate of patients with stroke. However, there is limited understanding about the factors associated with rehabilitation assessment among patients with intracerebral hemorrhage (ICH) in China. We aimed to investigate the factors associated with rehabilitation assessment in patients with ICH and the relationship between rehabilitation assessment and hospitalization outcomes. METHODS: Data from 85,664 patients with ICH admitted to 1,312 hospitals between 1 August 2015 and 31 July 2019 were analyzed. A multivariable logistic regression model accounting for in-hospital clustering was used to identify patient and hospital factors associated with rehabilitation assessment during acute hospitalization. RESULTS: A total of 62,228 (72.6%) patients with ICH underwent rehabilitation assessments. In multivariable analyses, factors associated with an increased likelihood of undergoing a rehabilitation assessment (P < .05) included a higher Glasgow Coma Scale score on admission, a history of hypertension, a history of peripheral vascular disease, dysphagia screening, carotid vessel imaging, and a longer length of hospital stay. Conversely, patients admitted to the intensive care unit and tertiary-grade hospitals were less likely to undergo rehabilitation assessments during hospitalization for ICH. DISCUSSION: This study showed that the rate of rehabilitation assessment was 74.2%, which is low. Rehabilitation assessment was associated with longer hospital stays and lower mortality. Therefore, patients with acute cerebral haemorrhage should undergo comprehensive and professional rehabilitation assessment.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study.

Background: The tumor immune microenvironment (TIME) phenotypes have been reported to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy in cancers, knowing an individual's TIME phenotypes could be helpful in screening patients who are more likely to respond to immunotherapy. Our study intended to establish, validate, and apply a machine learning model to predict TIME profiles in non-small cell lung cancer (NSCLC) by using 18F-FDG PET/CT radiomics and clinical characteristics. Methods: The RNA-seq data of 1145 NSCLC patients from The Cancer Genome Atlas (TCGA) cohort were analyzed. Then, 221 NSCLC patients from Daping Hospital (DPH) cohort received18F-FDG PET/CT scans before treatment and CD8 expression of the tumor samples were tested. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images and develop a radiomics signature. The models were established by radiomics, clinical features, and radiomics-clinical combination, respectively, the performance of which was calculated by receiver operating curves (ROCs) and compared by DeLong test. Moreover, based on radiomics score (Rad-score) and clinical features, a nomogram was established. Finally, we applied the combined model to evaluate TIME phenotypes of NSCLC patients in The Cancer Imaging Archive (TCIA) cohort (n = 39). Results: TCGA data showed CD8 expression could represent the TIME profiles in NSCLC. In DPH cohort, PET/CT radiomics model outperformed CT model (AUC: 0.907 vs. 0.861, P = 0.0314) to predict CD8 expression. Further, PET/CT radiomics-clinical combined model (AUC = 0.932) outperformed PET/CT radiomics model (AUC = 0.907, P = 0.0326) or clinical model (AUC = 0.868, P = 0.0036) to predict CD8 expression. In the TCIA cohort, the predicted CD8-high group had significantly higher immune scores and more activated immune pathways than the predicted CD8-low group (P = 0.0421). Conclusion: Our study indicates that 18F-FDG PET/CT radiomics-clinical combined model could be a clinically practical method to non-invasively detect the tumor immune status in NSCLCs.

CT Texture Analysis for Differentiating Bronchiolar Adenoma, Adenocarcinoma In Situ, and Minimally Invasive Adenocarcinoma of the Lung.

Purpose: This study aimed to investigate the potential of computed tomography (CT) imaging features and texture analysis to distinguish bronchiolar adenoma (BA) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Materials and Methods: Fifteen patients with BA, 38 patients with AIS, and 36 patients with MIA were included in this study. Clinical data and CT imaging features of the three lesions were evaluated. Texture features were extracted from the thin-section unenhanced CT images using Artificial Intelligence Kit software. Then, multivariate logistic regression analysis based on selected texture features was employed to distinguish BA from AIS/MIA. Receiver operating characteristics curves were performed to determine the diagnostic performance of the features. Results: By comparison with AIS/MIA, significantly different CT imaging features of BA included nodule type, tumor size, and pseudo-cavitation sign. Among them, pseudo-cavitation sign had a moderate diagnostic value for distinguishing BA and AIS/MIA (AUC: 0.741 and 0.708, respectively). Further, a total of 396 quantitative texture features were extracted. After comparation, the top six texture features showing the most significant difference between BA and AIS or MIA were chosen. The ROC results showed that these key texture features had a high diagnostic value for differentiating BA from AIS or MIA, among which the value of a comprehensive model with six selected texture features was the highest (AUC: 0.977 or 0.976, respectively) for BA and AIS or MIA. These results indicated that texture analyses can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA. Conclusion: CT texture analysis can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA, which has a potential clinical value and helps pathologist and clinicians to make diagnostic and therapeutic strategies.

18F-FDG PET Combined With MR Spectroscopy Elucidates the Progressive Metabolic Cerebral Alterations After Blast-Induced Mild Traumatic Brain Injury in Rats.

A majority of blast-induced mild traumatic brain injury (mTBI) patients experience persistent neurological dysfunction with no findings on conventional structural MR imaging. It is urgent to develop advanced imaging modalities to detect and understand the pathophysiology of blast-induced mTBI. Fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG PET) could detect neuronal function and activity of the injured brain, while MR spectroscopy provides complementary information and assesses metabolic irregularities following injury. This study aims to investigate the effectiveness of combining 18F-FDG PET with MR spectroscopy to evaluate acute and subacute metabolic cerebral alterations caused by blast-induced mTBI. Thirty-two adult male Sprague-Dawley rats were exposed to a single blast (mTBI group) and 32 rats were not exposed to the blast (sham group), followed by 18F-FDG PET, MRI, and histological evaluation at baseline, 1-3 h, 1 day, and 7 days post-injury in three separate cohorts. 18F-FDG uptake showed a transient increase in the amygdala and somatosensory cortex, followed by a gradual return to baseline from day 1 to 7 days post-injury and a continuous rise in the motor cortex. In contrast, decreased 18F-FDG uptake was seen in the midbrain structures (inferior and superior colliculus). Analysis of MR spectroscopy showed that inflammation marker myo-inositol (Ins), oxidative stress marker glutamine + glutamate (Glx), and hypoxia marker lactate (Lac) levels markedly elevated over time in the somatosensory cortex, while the major osmolyte taurine (Tau) level immediately increased at 1-3 h and 1 day, and then returned to sham level on 7 days post-injury, which could be due to the disruption of the blood-brain barrier. Increased 18F-FDG uptake and elevated Ins and Glx levels over time were confirmed by histology analysis which showed increased microglial activation and gliosis in the frontal cortex. These results suggest that 18F-FDG PET and MR spectroscopy can be used together to reflect more comprehensive neuropathological alterations in vivo, which could improve our understanding of the complex alterations in the brain after blast-induced mTBI.

Paclitaxel inhibits proliferation and invasion and promotes apoptosis of breast cancer cells by blocking activation of the PI3K/AKT signaling pathway.

BACKGROUND: Breast cancer has the highest incidence and mortality among all cancers in women. Paclitaxel (PTX) has a notable therapeutic effect on cancer in clinical practice. OBJECTIVES: To explore the effect and mechanism of PTX on the proliferation, apoptosis and invasiveness of breast cancer cells. MATERIAL AND METHODS: MCF-7 cells were treated with PTX (0 µM, 0.01 µM, 0.1 µM, 1 µM) for 48 h. Cell viability was detected using MTT assay and lactate dehydrogenase (LDH) assay; the cell proliferation rate was detected using 5-ethynyl-2'-deoxyuridine (EdU) assay to screen the most effective concentration of PTX. MCF-7 cells were then divided into 5 groups: control group, PTX group, oe-PI3K group, NC-PI3K group, and oe-PI3K+PTX group. Cell apoptosis and cell cycles were detected with flow cytometry; cell invasion was determined using a transwell assay; western blot and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) were used to measure the mRNA and protein expression level of cleaved caspase-3, Bax, Bcl-2, matrix metalloproteinase 9 (MMP-9), vascular endothelial growth factor (VEGF), p-AKT (Thr308), and p-AKT (Ser473). RESULTS: Paclitaxel inhibited cell viability and proliferation in a dose-dependent manner. In the PTX group, the apoptosis rate, the number of cells arrested in the G2/M phase and the expression levels of Cleaved caspase-3 and Bax were increased, but the number of invasive cells and the expression levels of Bcl-2, MMP-9, vascular endothelial growth factor (VEGF), p-AKT (Thr308), and p-AKT (Ser473) were decreased. However, PI3K upregulation can reverse the effects of PTX. CONCLUSIONS: Paclitaxel could inhibit MCF-7 cell proliferation and invasion, and promote MCF-7 cell apoptosis by downregulating the expression of p-AKT (Thr308) and p-AKT (Ser473) in the PI3K/AKT signaling pathway.

White Matter Atrophy in Type 2 Diabetes Mellitus Patients With Mild Cognitive Impairment.

Type 2 diabetes mellitus (T2DM) patients are highly susceptible to developing dementia, especially for those with mild cognitive impairment (MCI), but its underlying cause is still unclear. In this study, we performed a battery of neuropsychological tests and high-resolution sagittal T1-weighted structural imaging to explore how T2DM affects white matter volume (WMV) and cognition in 30 T2DM-MCI patients, 30 T2DM with normal cognition (T2DM-NC) patients, and 30 age-, sex-, and education-matched healthy control (HC) individuals. The WMV of the whole brain was obtained with automated segmentation methods. Correlations between the WMV of each brain region and neuropsychological tests were analyzed in the T2DM patients. The T2DM-NC patients and HC individuals did not reveal any significant differences in WMV. Compared with the T2DM-NC group, the T2DM-MCI group showed statistically significant reduction in the WMV of seven brain regions, mainly located in the frontotemporal lobe and limbic system, five of which significantly correlated with Montreal Cognitive Assessment (MoCA) scores. Subsequently, we evaluated the discriminative ability of these five regions for MCI in T2DM patients. The WMV of four regions, including left posterior cingulate, precuneus, insula, and right rostral middle frontal gyrus had high diagnostic value for MCI detection in T2DM patients (AUC > 0.7). Among these four regions, left precuneus WMV presented the best diagnostic value (AUC: 0.736; sensitivity: 70.00%; specificity: 73.33%; Youden index: 0.4333), but with no significant difference relative to the minimum AUC. In conclusion, T2DM could give rise to the white matter atrophy of several brain regions. Each WMV of left posterior cingulate, precuneus, insula, and right rostral middle frontal gyrus could be an independent imaging biomarker to detect cognitive impairment at the early stage in T2DM patients and play an important role in its pathophysiological mechanism.

A Numerical Study of Micro-Droplet Spreading Behaviors on Wettability-Confined Tracks Using a Three-Dimensional Phase-Field Lattice Boltzmann Model.

Wettability-confined tracks have been extensively used in open-surface microfluidic devices for their high capacity of transporting droplet pumplessly. Inspired by the experimental work of Sen et al. [ Langmuir 2018 , 34 , 1899 - 1907 ], in the present study, a three-dimensional phase-field lattice Boltzmann model is developed and used to investigate the spreading behaviors of microdroplet on a series of wettability-confined tracks. The experimental findings are successfully reproduced through our simulation, where three distinct stages of droplet spreading on the horizontal wettability-confined diverging track are fairly exhibited, that is, the initial stage with droplet front spreading quickly, the intermediate stage with both droplet front and bulge moving forward at a constant speed, and the final stage with droplet front decelerating gradually. Moreover, a parametric study of track divergence angle is further performed, and the influential mechanism of track divergence angle on droplet spreading is further revealed. It is demonstrated that track divergence is responsible for the Laplace pressure gradient and capillary force inside the droplet, which drives the droplet bulge to move forward on the diverging track. With an increase in divergence angle, the capillary force increases linearly, which increases the droplet spreading speed at the initial and intermediate stages, while the peak capillary force comes earlier, and consequently the final decelerating stage comes earlier. On the basis of the parametric study and droplet volume conservation rule, a power law relation between track divergence angle and droplet spreading is proposed, which helps to identify the start of final decelerating stage. Finally, the droplet spreading over various inclined tracks is explored, which can be achieved only when the capillary force at the beginning is larger than the droplet gravity component along the inclined track surface.

A numerical study of droplet dynamic behaviors on a micro-structured surface using a three dimensional color-gradient lattice Boltzmann model.

Inspired by the experimental work of Raj et al. (high-resolution liquid patterns via three-dimensional droplet shape control), in the present study, a three-dimensional multiphase color-gradient lattice Boltzmann model developed previously by some of the authors is used to simulate droplet dynamic behaviors with different surface micro-pillar arrays. To facilitate the present simulation, wetting boundary conditions are used and the accuracy of color gradient prediction at boundary nodes is enhanced. The experimental findings are confirmed and non-circular contact lines are reproduced numerically for the first time. To justify the existing contact angle formula proposed based on the Wenzel model, a systematic parametric study is conducted, based on which the pillar density is redefined to allow for the influence of pillar height, and then it is used to modify the contact angle. In addition, the evolution of the contact line motion for various droplet shapes is investigated systematically, and both circular and non-circular contact characteristics are well-depicted for different surface micro-pillar arrays.

Hybrid Dielectric-loaded Nanoridge Plasmonic Waveguide for Low-Loss Light Transmission at the Subwavelength Scale.

The emerging development of the hybrid plasmonic waveguide has recently received significant attention owing to its remarkable capability of enabling subwavelength field confinement and great transmission distance. Here we report a guiding approach that integrates hybrid plasmon polariton with dielectric-loaded plasmonic waveguiding. By introducing a deep-subwavelength dielectric ridge between a dielectric slab and a metallic substrate, a hybrid dielectric-loaded nanoridge plasmonic waveguide is formed. The waveguide features lower propagation loss than its conventional hybrid waveguiding counterpart, while maintaining strong optical confinement at telecommunication wavelengths. Through systematic structural parameter tuning, we realize an efficient balance between confinement and attenuation of the fundamental hybrid mode, and we demonstrate the tolerance of its properties despite fabrication imperfections. Furthermore, we show that the waveguide concept can be extended to other metal/dielectric composites as well, including metal-insulator-metal and insulator-metal-insulator configurations. Our hybrid dielectric-loaded nanoridge plasmonic platform may serve as a fundamental building block for various functional photonic components and be used in applications such as sensing, nanofocusing, and nanolasing.

Multiple-relaxation-time color-gradient lattice Boltzmann model for simulating two-phase flows with high density ratio.

In this paper we propose a color-gradient lattice Boltzmann (LB) model for simulating two-phase flows with high density ratio and high Reynolds number. The model applies a multirelaxation-time (MRT) collision operator to enhance the stability of the simulation. A source term, which is derived by the Chapman-Enskog analysis, is added into the MRT LB equation so that the Navier-Stokes equations can be exactly recovered. Also, a form of the equilibrium density distribution function is used to simplify the source term. To validate the proposed model, steady flows of a static droplet and the layered channel flow are first simulated with density ratios up to 1000. Small values of spurious velocities and interfacial tension errors are found in the static droplet test, and improved profiles of velocity are obtained by the present model in simulating channel flows. Then, two cases of unsteady flows, Rayleigh-Taylor instability and droplet splashing on a thin film, are simulated. In the former case, the density ratio of 3 and Reynolds numbers of 256 and 2048 are considered. The interface shapes and spike and bubble positions are in good agreement with the results of previous studies. In the latter case, the droplet spreading radius is found to obey the power law proposed in previous studies for the density ratio of 100 and Reynolds number up to 500.

Color-gradient lattice Boltzmann model for simulating droplet motion with contact-angle hysteresis.

Lattice Boltzmann method (LBM) is an effective tool for simulating the contact-line motion due to the nature of its microscopic dynamics. In contact-line motion, contact-angle hysteresis is an inherent phenomenon, but it is neglected in most existing color-gradient based LBMs. In this paper, a color-gradient based multiphase LBM is developed to simulate the contact-line motion, particularly with the hysteresis of contact angle involved. In this model, the perturbation operator based on the continuum surface force concept is introduced to model the interfacial tension, and the recoloring operator proposed by Latva-Kokko and Rothman is used to produce phase segregation and resolve the lattice pinning problem. At the solid surface, the color-conserving wetting boundary condition [Hollis et al., IMA J. Appl. Math. 76, 726 (2011)] is applied to improve the accuracy of simulations and suppress spurious currents at the contact line. In particular, we present a numerical algorithm to allow for the effect of the contact-angle hysteresis, in which an iterative procedure is used to determine the dynamic contact angle. Numerical simulations are conducted to verify the developed model, including the droplet partial wetting process and droplet dynamical behavior in a simple shear flow. The obtained results are compared with theoretical solutions and experimental data, indicating that the model is able to predict the equilibrium droplet shape as well as the dynamic process of partial wetting and thus permits accurate prediction of contact-line motion with the consideration of contact-angle hysteresis.