Development of interpenetrating network hydrogels: Enhancing the release and bioaccessibility of green tea polyphenols.

Green Tea polyphenols (GTP) are important bioactive compounds with excellent physiological regulation functions. However, they are easily destroyed by the gastric environment during digestion. In this work, a sodium alginate (SA)-gellan gum (GG) interpenetrating network (IPN) hydrogel was synthesized to protect and delivery GTP. The ratio of SA/GG significantly affects the network structure of IPN hydrogels and the performance of delivering GTP. The hydrogel formed by interpenetrating 20 % GG with 80 % SA as the main network had the highest water uptake (55 g/g), holding capacity (950 mg/g), and freeze-thaw stability, with springiness reaching 0.933 and hardness reaching 1300 g, which due to the filling effect and non-covalent interaction. Rheological tests showed that the crosslink density of IPN hydrogel in SA-dominated network was improved by the addition of GG to make it better bound to GTP, and the higher water uptake meant that the system could absorb more GTP-containing solution. This IPN hydrogel maintained 917.3 mg/g encapsulation efficiency at the highest loading capacity (1080 mg/g) in tests as delivery system. In in vitro digestion simulations, owing to the pH responsiveness, the IPN hydrogel reduced the loss of GTP in gastric fluid, achieving a bioaccessibility of 71.6 % in the intestinal tract.

Biomimetic Nanovesicles as a Dual Gene Delivery System for the Synergistic Gene Therapy of Alzheimer's Disease.

The association between dysfunctional microglia and amyloid-ß (Aß) is a fundamental pathological event and increases the speed of Alzheimer's disease (AD). Additionally, the pathogenesis of AD is intricate and a single drug may not be enough to achieve a satisfactory therapeutic outcome. Herein, we reported a facile and effective gene therapy strategy for the modulation of microglia function and intervention of Aß anabolism by ROS-responsive biomimetic exosome-liposome hybrid nanovesicles (designated as TSEL). The biomimetic nanovesicles codelivery ß-site amyloid precursor protein cleaving enzyme-1 (BACE1) siRNA (siBACE1) and TREM2 plasmid (pTREM2) gene drug efficiently penetrate the blood-brain barrier and enhance the drug accumulation at AD lesions with the help of exosomes homing ability and angiopep-2 peptides. Specifically, an upregulation of TREM2 expression can reprogram microglia from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype while also restoring its capacity to phagocytose Aß and its nerve repair function. In addition, siRNA reduces the production of Aß plaques at the source by knocking out the BACE1 gene, which is expected to further enhance the therapeutic effect of AD. The in vivo study suggests that TSEL through the synergistic effect of two gene drugs can ameliorate APP/PS1 mice cognitive impairment by regulating the activated microglial phenotype, reducing the accumulation of Aß, and preventing the retriggering of neuroinflammation. This strategy employs biomimetic nanovesicles for the delivery of dual nucleic acids, achieving synergistic gene therapy for AD, thus offering more options for the treatment of AD.

On-Line pH Measurement Cation Exchange Kinetics of Y3+-Exchanged Alginic Acid for Y2O3 Nanoparticles Synthesis.

A new sol-gel method that employs cation exchange from an aqueous metal ion solution with H+ ions of granulated alginic acid was developed for synthesizing high-purity Y2O3 nanoparticles. In this study, the cation exchange kinetics of H+~Y3+ in aqueous solution were analyzed using on-line pH technology and off-line inductively coupled plasma-atomic emission spectrometry (ICP-AES) analysis. Pseudo 2nd-order models were utilized to evaluate the parameters of the kinetics, suggesting that the concentration of H+~Y3+ involved in the cation exchange reaction was 1:1.733. Further, a comprehensive understanding of the Y-ALG calcination process was developed using thermo-gravimetric analysis, along with results obtained from differential scanning calorimetry (TGA/DSC). A detailed analysis of the XRD Rietveld refinement plots revealed that the crystallite sizes of Y2O3 nanoparticles were about 4 nm (500 °C) and 15 nm (800 °C), respectively. Differential pulse voltammetry (DPV) was employed to investigate the electrochemical oxidation of catechol. The oxidation peak currents of catechol at Y2O3 (500 °C)/GCE and Y2O3 (800 °C)/GCE showed two stages linear function of concentration (2.0~20.0 × 10-6 mol/L, 20.0~60.0 × 10-6 mol/L). The results indicated that the detection limits were equal to 2.4 × 10-7 mol/L (Y2O3 (500 °C)/GCE) and 7.8 × 10-7 mol/L (Y2O3 (800 °C)/GCE). The study not only provided a method to synthesize metal oxide, but also proposed a promising on-line pH model to study cation exchange kinetics.

Chitosan oligosaccharide-functionalized nano-prodrug for cascade chemotherapy through oxidative stress amplification.

Redox nanoparticles have been extensively developed for chemotherapy. However, the intracellular oxidative stress induced by constant aberrant glutathione (GSH), reactive oxygen species (ROS) and gamma-glutamyl transpeptidase (GGT) homeostasis remains the primary cause of evading tumor apoptosis. Herein, an oxidative stress-amplification strategy was designed using a pH-GSH-H2O2-GGT sensitive nano-prodrug for precise synergistic chemotherapy. The disulfide bond- conjugated doxorubicin prodrug (DOX-ss) was constructed as a GSH-scavenger. Then, phenylboronic acid (PBA), DOX-ss and poly (γ-glutamic acid) (γ-PGA) were successively conjugated using chitosan oligosaccharide (COS) to obtain the nano-prodrug PBA-COS-ss-DOX/γ-PGA. The PBA-COS-ss-DOX/γ-PGA prodrug could tightly attach to the polymer chain segment by atom transfer radical polymerization. Simultaneously, the drug interacted relatively weakly with the polymer by encapsulating ionic crosslinkers in DOX@PBA-COS/γ-PGA. The disulfide bond of the DOX-ss prodrug as a GSH-scavenger could be activated using overexpressed GSH to release DOX. Particularly, PBA-COS-ss-DOX/γ-PGA could prevent premature drug leakage and facilitate DOX delivery by GGT-targeting and intracellular H2O2-cleavable linker in human hepatocellular carcinoma (HepG2) cells. Concurrently, the nano-prodrug induced strong oxidative stress and tumor cell apoptosis. Collectively, the pH-GSH-H2O2-GGT responsive nano-prodrug shows potential for synergistic tumor therapy.

Lenvatinib Combined with the PD-1 Inhibitor Camrelizumab in the Treatment of Primary Liver Cancer Caused Hemorrhagic Exfoliative Gastritis.

Introduction: Patients with advanced primary liver cancer often lose the opportunity for surgery when they are found, and the treatment options are limited. Lenvatinib, as a multi-target tyrosine kinase inhibitor, has been used as the first-line treatment for advanced liver cancer. Immune checkpoint inhibitors, such as programmed cell death protein 1 inhibitors, have been successfully used in advanced or metastatic liver cancer. Case Presentation: We report a case of combined lenvatinib and the programmed cell death protein 1 inhibitor camrelizumab in the treatment of primary liver cancer, in which the rare complication of full-thickness gastric mucosa exfoliation occurred. To the best of our knowledge, this is the first report of the side effect of hemorrhagic exfoliative gastritis with the combination of lenvatinib and camrelizumab. Conclusion: Hemorrhagic exfoliative gastritis is an extremely rare clinical complication. Lenvatinib inhibits vascular proliferation and could cause gastrointestinal perforation, which is considered to be the main factor, but whether camrelizumab plays a role in it or only causes gastrointestinal reactions leading to nausea and vomiting, resulting in gastric mucosal exfoliation bleeding, remains to be further explored.

MSNSegNet: attention-based multi-shape nuclei instance segmentation in histopathology images.

In clinical research, the segmentation of irregularly shaped nuclei, particularly in mesenchymal areas like fibroblasts, is crucial yet often neglected. These irregular nuclei are significant for assessing tissue repair in immunotherapy, a process involving neovascularization and fibroblast proliferation. Proper segmentation of these nuclei is vital for evaluating immunotherapy's efficacy, as it provides insights into pathological features. However, the challenge lies in the pronounced curvature variations of these non-convex nuclei, making their segmentation more difficult than that of regular nuclei. In this work, we introduce an undefined task to segment nuclei with both regular and irregular morphology, namely multi-shape nuclei segmentation. We propose a proposal-based method to perform multi-shape nuclei segmentation. By leveraging the two-stage structure of the proposal-based method, a powerful refinement module with high computational costs can be selectively deployed only in local regions, improving segmentation accuracy without compromising computational efficiency. We introduce a novel self-attention module to refine features in proposals for the sake of effectiveness and efficiency in the second stage. The self-attention module improves segmentation performance by capturing long-range dependencies to assist in distinguishing the foreground from the background. In this process, similar features get high attention weights while dissimilar ones get low attention weights. In the first stage, we introduce a residual attention module and a semantic-aware module to accurately predict candidate proposals. The two modules capture more interpretable features and introduce additional supervision through semantic-aware loss. In addition, we construct a dataset with a proportion of non-convex nuclei compared with existing nuclei datasets, namely the multi-shape nuclei (MsN) dataset. Our MSNSegNet method demonstrates notable improvements across various metrics compared to the second-highest-scoring methods. For all nuclei, the D i c e score improved by approximately 1.66 % , A J I by about 2.15 % , and D i c e obj by roughly 0.65 % . For non-convex nuclei, which are crucial in clinical applications, our method's A J I improved significantly by approximately 3.86 % and D i c e obj by around 2.54 % . These enhancements underscore the effectiveness of our approach on multi-shape nuclei segmentation, particularly in challenging scenarios involving irregularly shaped nuclei.

A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma.

PURPOSE: To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features. METHODS: A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves. RESULTS: The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076). CONCLUSIONS: Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.

Preparation and Characterization of Multielement Composite Oxide Nanomaterials Containing Ce, Zr, Y, and Yb via Continuous Hydrothermal Flow Synthesis.

The synthesis of multielement composite oxide nanomaterials containing Ce, Zr, Y, and Yb was investigated using a micro confined jet mixer reactor operated in continuous mode under supercritical water conditions. The obtained nanoparticles were characterized using ICP-AES, SEM-EDS, FTIR, Raman spectroscopy, XRD, and TEM. All samples exhibited a uniform particle shape and a narrow particle size distribution. An analysis of the d-spacing results using selected electron area diffraction (SAED) patterns confirmed the production of cubic-phase crystals. A BET test was employed to determine the specific surface area of the prepared nanoparticles. OSC and TPR techniques were utilized to characterize the oxygen storage capacity and reduction performance of the obtained samples, with an analysis conducted to determine how the different proportions of elements affected the performance of multielement mixed oxides. The ionic conductivity of multielement composite oxide was measured using alternating current impedance spectroscopy (EIS), and the impact of Y, Ce, and Yb on the electrolyte material's ionic conductivity was analyzed.

Microarray-Based CD38 Peptide Probe Screening for Multiple Myeloma Imaging.

Assessing CD38 expression in vivo has become a significant element in multiple myeloma (MM) therapy, as it can be used to detect lesions and forecast the effectiveness of treatment. Accurate diagnosis requires a multifunctional, high-throughput probe screening platform to develop molecular probes for tumor-targeted multimodal imaging and treatment. Here, we investigated a microarray chip-based strategy for high-throughput screening of peptide probes for CD38. We obtained two new target peptides, CA-1 and CA-2, from a 105 peptide library with a dissociation constant (KD) of 10-7 M. The specificity and affinity of the target peptides were confirmed at the molecular and cellular levels. Peptide probes were labeled with indocyanine green (ICG) dye and 68Ga-DOTA, which were injected into a CD38-positive Ramos tumor-bearing mouse via its tail vein, and small animal fluorescence and positron emission tomography (PET) imaging showed that the peptide probes could show specific enrichment in the tumor tissue. Our study shows that a microchip-based screening of peptide probes can be used as a promising imaging tool for MM diagnosis.

Disordered Convolution Region of P(VDF-TrFE) Piezoelectric Nanoparticles: The Core of Sono-Piezo Dynamic Therapy.

The recent focus on P(VDF-TrFE) material in biomedical engineering stems from its outstanding mechanical properties and biocompatibility. However, its application in sono-piezo dynamic therapy (SPDT) has been relatively unexplored. In this study, we developed composite piezoelectric nanoparticles (rPGd NPs@RGD) based on recrystallized P(VDF-TrFE) particles, which offer dual capabilities of MRI imaging and targeted treatment for brain gliomas. SEM observations of P(VDF-TrFE) particles in the disordered convolution region (DCR) revealed recrystallization, representing the polymer chain structure and particle polarity. In comparison to nonrecrystallized nanoparticles, rPGd NPs@RGD exhibited remarkable stability and biocompatibility. Under ultrasound excitation, they generated significantly higher levels of reactive oxygen species, effectively inhibiting tumor cell proliferation, invasion, and migration. rPGd NPs@RGD demonstrated excellent MRI imaging capabilities and antitumor activity in U87 tumor-bearing mice. This study highlights the remarkable SPDT abilities of the developed nanoparticles, attributed to the microscopic morphological changes in the DCR that increase the nanoparticle's polarity and thus boost its potential for SPDT. This research opens new possibilities for utilizing P(VDF-TrFE) materials in advanced biomedical applications.

Altered rumen microbiome and correlations of the metabolome in heat-stressed dairy cows at different growth stages.

IMPORTANCE: Heat stress is one of the main causes of economic losses in the dairy industry worldwide; however, the mechanisms associated with the metabolic and microbial changes in heat stress remain unclear. Here, we characterized both the changes in metabolites, rumen microbial communities, and their functional potential indices derived from rumen fluid and serum samples from cows at different growth stages and under different climates. This study highlights that the rumen microbe may be involved in the regulation of lipid metabolism by modulating the fatty acyl metabolites. Under heat stress, the changes in the metabolic status of growing heifers, heifers, and lactating cows were closely related to arachidonic acid metabolism, fatty acid biosynthesis, and energy metabolism. Moreover, this study provides new markers for further research to understand the effects of heat stress on the physiological metabolism of Holstein cows and the time-dependent changes associated with growth stages.

A Reactive Oxygen Species-Responsive Targeted Nanoscavenger to Promote Mitophagy for the Treatment of Alzheimer's Disease.

Mitophagy modulators are proposed as potential therapeutic intervention that enhance neuronal health and brain homeostasis in Alzheimer's disease (AD). Nevertheless, the lack of specific mitophagy inducers, low efficacies, and the severe side effects of nonselective autophagy during AD treatment have hindered their application. In this study, the P@NB nanoscavenger is designed with a reactive-oxygen-species-responsive (ROS-responsive) poly(l-lactide-co-glycolide) core and a surface modified with the Beclin1 and angiopoietin-2 peptides. Notably, nicotinamide adenine dinucleotide (NAD+ ) and Beclin1, which act as mitophagy promoters, are quickly released from P@NB in the presence of high ROS levels in lesions to restore mitochondrial homeostasis and induce microglia polarization toward the M2-type, thereby enabling it to phagocytose amyloid-peptide (Aß). These studies demonstrate that P@NB accelerates Aß degradation and alleviates excessive inflammatory responses by restoring autophagic flux, which ameliorates cognitive impairment in AD mice. This multitarget strategy induces autophagy/mitophagy through synergy, thereby normalizing mitochondrial dysfunction. Therefore, the developed method provides a promising AD-therapy strategy.

Phononically shielded photonic-crystal mirror membranes for cavity quantum optomechanics.

We present a highly reflective, sub-wavelength-thick membrane resonator featuring high mechanical quality factor and discuss its applicability for cavity optomechanics. The 88.5 nm thin stoichiometric silicon-nitride membrane, designed and fabricated to combine 2D-photonic and phononic crystal patterns, reaches reflectivities up to 99.89 % and a mechanical quality factor of 2.9 × 107 at room temperature. We construct a Fabry-Perot-type optical cavity, with the membrane forming one terminating mirror. The optical beam shape in cavity transmission shows a stark deviation from a simple Gaussian mode-shape, consistent with theoretical predictions. We demonstrate optomechanical sideband cooling to mK-mode temperatures, starting from room temperature. At higher intracavity powers we observe an optomechanically induced optical bistability. The demonstrated device has potential to reach high cooperativities at low light levels desirable, for example, for optomechanical sensing and squeezing applications or fundamental studies in cavity quantum optomechanics; and meets the requirements for cooling to the quantum ground state of mechanical motion from room temperature.

Cyclic Learning: Bridging Image-Level Labels and Nuclei Instance Segmentation.

Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manual annotations, which is especially time-consuming and laborious for the high nuclei density. To alleviate the annotation burden, we seek to solve the problem through image-level weakly supervised learning, which is underexplored for nuclei instance segmentation. Compared with most existing methods using other weak annotations (scribble, point, etc.) for nuclei instance segmentation, our method is more labor-saving. The obstacle to using image-level annotations in nuclei instance segmentation is the lack of adequate location information, leading to severe nuclei omission or overlaps. In this paper, we propose a novel image-level weakly supervised method, called cyclic learning, to solve this problem. Cyclic learning comprises a front-end classification task and a back-end semi-supervised instance segmentation task to benefit from multi-task learning (MTL). We utilize a deep learning classifier with interpretability as the front-end to convert image-level labels to sets of high-confidence pseudo masks and establish a semi-supervised architecture as the back-end to conduct nuclei instance segmentation under the supervision of these pseudo masks. Most importantly, cyclic learning is designed to circularly share knowledge between the front-end classifier and the back-end semi-supervised part, which allows the whole system to fully extract the underlying information from image-level labels and converge to a better optimum. Experiments on three datasets demonstrate the good generality of our method, which outperforms other image-level weakly supervised methods for nuclei instance segmentation, and achieves comparable performance to fully-supervised methods.

CFD-PBM Simulation for Continuous Hydrothermal Flow Synthesis of Zirconia Nanoparticles in a Confined Impinging Jet Reactor.

Computational fluid dynamics (CFD) and population balance models (PBM) were coupled together for the first time to simulate the synthesis of zirconia nanoparticles in a continuous hydrothermal flow synthesis (CHFS) system with a self-designed confined impinging jet mixing (CJM) reactor. The hydrodynamic and thermodynamic behaviors within the CJM reactor strongly influenced the formation of the ZrO2 nanoparticles. Crucial parameters, such as velocities, temperatures, mixing conditions, and reaction rates, were analyzed under various supercritical conditions. Temperature and velocity measurements as functions of distance were also investigated. Normal particle size distribution (PSD) patterns were observed in all cases. The mean particle sizes in this study were calculated and compared using PBM aggregation analysis.

A Novel Homodimer Peptide-Drug Conjugate Improves the Efficacy of HER2-Positive Breast Cancer Therapy.

Tumor-targeting peptide-drug conjugates (PDCs) have become a focus of research in recent years. However, due to the instability of peptides and their short in vivo effective half-life, they have limited clinical application. Herein, we propose a new DOX PDC based on a homodimer HER-2-targeting peptide and acid-sensitive hydrazone bond, which could enhance the anti-tumor effect of DOX and reduce systemic toxicities. The PDC could accurately deliver DOX into HER2-positive SKBR-3 cells, with it showing 2.9 times higher cellular uptake than free DOX and enhanced cytotoxicity with respect to IC50 of 140 nM (vs. 410 nM for free DOX). In vitro assays showed that the PDC had high cellular internalization efficiency and cytotoxicity. In vivo anti-tumor experiments indicated that the PDC could significantly inhibit the growth of HER2-positive breast cancer xenografts in mice and reduce the side effects of DOX. In summary, we constructed a novel PDC molecule targeting HER2-positive tumors, which may overcome some deficiencies of DOX in breast cancer therapy.

Clinical study of Tongdu Shujin decoction in the treatment of ankylosing spondylitis with cold-dampness obstruction type: Study protocol for a randomized controlled trial.

BACKGROUND: Ankylosing spondylitis (AS) has a high incidence, and severe cases can lead to spinal deformity and even joint fusion, which causes a huge burden on patients life, work and psychology. Tongdu Shujin decoction (TDSJ) has a definite effect in the treatment of ankylosing spondylitis, so we designed a randomized controlled trial to observe the efficacy of TDSJ in the treatment of AS, and to evaluate its safety. METHODS: In this randomized controlled trial, 80 eligible patients were randomly assigned in a 1:1 ratio to a treatment group TDSJ and a control group (celecoxib capsules in combination with thalidomide tablets) for 8 weeks. Visual analogue scale, bath ankylosing spondylitis disease activity index, bath ankylosing spondylitis functional index, and traditional Chinese medicine syndrome scores will be used as primary indicators. Erythrocyte sedimentation rate, C-reactive protein, spinal mobility (figure-ground distance, occipital tubercle-wall distance, Schober test) will be used as secondary indicators. Vital signs (respiration, heart rate, body temperature, blood pressure, electrocardiogram), blood routine, urine routine, stool routine, liver function, and renal function will be used as safety indicators. The primary and secondary indicators will be detected at 0th and 8th week, while safety indicators at 0th, 4th, and 8th week. DISCUSSION: This study will provide high-quality clinical evidence for the efficacy and safety of TDSJ in the treatment of AS.

A Totipotent "All-In-One" Peptide Sequentially Blocks Immune Checkpoint and Reverses the Immunosuppressive Tumor Microenvironment.

Immune checkpoint blockade combined with reversal of the immunosuppressive tumor microenvironment (TME) can dramatically enhance anti-tumor immunity, which can be achieved by using multiple-agent therapy. However, the optimal dose and order of administration of different agents remain elusive. To address this dilemma, multiple agents are often grafted together to construct "all-in-one" totipotent drugs, but this usually comes at the cost of a lack of synergy between the agents. Herein, by comprehensively analyzing the conserved sites of the immune checkpoint and TME drug targets, peptide secondary structures, assembly properties, and other physicochemical properties, a high-content peptide library is designed. By using the "3D-molecular-evolution" screening strategy, an efficient and totipotent "all-in-one" peptide (TAP) is obtained, which possesses the abilities of self-assembling, blocking the PD-1/PD-L1 axis, inhibiting Rbm38-eIF4E complex formation, and activating p53. It is shown that in mice treated with TAP, with either subcutaneous tumors or patient-derived xenografts, PD-L1 is blocked, with increased activation of both T and NK cells whilst reversing the immunosuppressive TME. Moreover, TAP can mitigate tumor activity and suppress tumor growth, showing superior therapeutic effect over antibody-based drugs.

Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma.

BACKGROUND: Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options. PURPOSE: To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC). MATERIAL AND METHODS: A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve. RESULTS: Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; P = 0.008) and MRI (0.946 vs. 0.876; P = 0.003), whereas rim APHE on CT and MRI did not differ significantly (P = 0.809). CONCLUSION: The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.