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Background: Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis. Magnetic resonance imaging (MRI) is one of the most effective imaging methods for the early diagnosis of HCC. However, the current MR contrast agents are still facing challenges in the early diagnosis of HCC due to their relatively low sensitivity and biosafety. Thus, the development of effective MR agents is highly needed for the early diagnosis of HCC., Results: Herein, we fabricated an HCC-targeted nanocomplexes containing SPIO-loaded mesoporous polydopamine (MPDA@SPIO), sialic acid (SA)-modified polyethyleneimine (SA-PEI), and alpha-fetoprotein regulated ferritin gene (AFP-Fth) which was developed for the early diagnosis of HCC. It was found that the prepared nanocomplexes (MPDA@SPIO/SA-PEI/AFP-Fth) has an excellent biocompatibility towards the liver cells. In vivo and in vivo studies revealed that the transfection of AFP-Fth gene in hepatic cells significantly upregulated the expression level of ferritin, thereby resulting in an enhanced contrast on T2-weighted images via the formed endogenous MR contrast., Conclusions: The results suggested that MPDA@SPIO/SA-PEI/AFP-Fth had a superior ability to enhance the MR contrast of T2-weighted images of tumor region than the other preparations, which was due to its HCC-targeted ability and the combined T2 contrast effect of endogenous ferritin and exogenous SPIO. Our study proved that MPDA@SPIO/SA-PEI/AFP-Fth nanocomplexes could be used as an effective MR contrast agent to detect HCC in the early stage.

Transcatheter arterial chemoembolization (TACE) is one of the main palliative therapies for advanced hepatocellular carcinoma (HCC), which is also regarded as a promising therapeutic strategy for cancer treatment. However, drug-loaded microspheres (DLMs), as commonly used clinical chemoembolization drugs, still have the problems of uneven particle size and unstable therapeutic efficacy. Herein, gelatin was used as the wall material of the microspheres, and homogenous gelatin microspheres co-loaded with adriamycin and Fe3O4 nanoparticles (ADM/Fe3O4-MS) were further prepared by a high-voltage electrospray technology. The introduction of Fe3O4 nanoparticles into DLMs not only provided excellent T2-weighted magnetic resonance imaging (MRI) properties, but also improved the anti-tumor effectiveness under microwave-induced hyperthermia. The results showed that ADM/Fe3O4-MS plus microwave irradiation had significantly better antitumor efficacy than the other types of microspheres at both cell and animal levels. Our study further confirmed that ferroptosis was involved in the anti-tumor process of ADM/Fe3O4-MS plus microwave irradiation, and ferroptosis marker GPX4 was significantly decreased and ACSL4 was significantly increased, and ferroptosis inhibitors could reverse the tumor cell killing effect caused by ADM/Fe3O4-MS to a certain extent. Our results confirmed that microwave mediated hyperthermia could amplify the antitumor efficacy of ADM/Fe3O4-MS by activating ferroptosis and the introduction of Fe3O4 nanoparticles can significantly improve TACE for HCC. This study confirmed that it was feasible to use uniform-sized gelatin microspheres co-loaded with Fe3O4 nanoparticles and adriamycin to enhance the efficacy of TACE for HCC. [ABSTRACT FROM AUTHOR]

Objectives: To construct a precise prediction model of preoperative magnetic resonance imaging (MRI)-based nomogram for aggressive intrasegmental recurrence (AIR) of hepatocellular carcinoma (HCC) patients treated with radiofrequency ablation (RFA).Methods: Among 891 patients with HCC treated by RFA, 22 patients with AIR and 36 patients without AIR (non-AIR) were finally enrolled in our study, and each patient was followed up for more than 6 months to determine the occurrence of AIR. The laboratory indicators and MRI features were compared and assessed. Preoperative contrast-enhanced T1-weighted images (CE-T1WI) were used for radiomics analysis. The selected clinical indicators and texture features were finally screened out to generate the novel prediction nomogram.Results: Tumor shape, ADC Value, DWI signal intensity and ΔSI were selected as the independent factors of AIR by univariate and multivariate logistic regression analysis. Meanwhile, two radiomics features were selected from 396 candidate features by LASSO (P < 0.05), which were further used to calculate the Rad-score. The selected clinical factors were further integrated with the Rad-score to construct the predictive model, and the AUCs were 0.941 (95% CI: 0.876-1.000) and 0.818 (95% CI: 0.576-1.000) in the training (15 AIR and 25 non-AIR) and validation cohorts (7 AIR and 11 non-AIR), respectively. The AIR predictive model was further converted into a novel radiomics nomogram, and decision curve analysis showed good agreement.Conclusions: The predictive nomogram integrated with clinical factors and CE-T1WI -based radiomics signature could accurately predict the occurrence of AIR after RFA, which could greatly help individualized evaluation before treatment. [ABSTRACT FROM AUTHOR]