Potentiating dual-directional immunometabolic regulation with nanomedicine to enhance anti-tumor immunotherapy following incomplete photothermal ablation.

Photothermal therapy (PTT) is a promising cancer treatment method due to its ability to induce tumor-specific T cell responses and enhance therapeutic outcomes. However, incomplete PTT can leave residual tumors that often lead to new metastases and decreased patient survival in clinical scenarios. This is primarily due to the release of ATP, a damage-associated molecular pattern that quickly transforms into the immunosuppressive metabolite adenosine by CD39, prevalent in the tumor microenvironment, thus promoting tumor immune evasion. This study presents a photothermal nanomedicine fabricated by electrostatic adsorption among the Fe-doped polydiaminopyridine (Fe-PDAP), indocyanine green (ICG), and CD39 inhibitor sodium polyoxotungstate (POM-1). The constructed Fe-PDAP@ICG@POM-1 (FIP) can induce tumor PTT and immunogenic cell death when exposed to a near-infrared laser. Significantly, it can inhibit the ATP-adenosine pathway by dual-directional immunometabolic regulation, resulting in increased ATP levels and decreased adenosine synthesis, which ultimately reverses the immunosuppressive microenvironment and increases the susceptibility of immune checkpoint blockade (aPD-1) therapy. With the aid of aPD-1, the dual-directional immunometabolic regulation strategy mediated by FIP can effectively suppress/eradicate primary and distant tumors and evoke long-term solid immunological memory. This study presents an immunometabolic control strategy to offer a salvage option for treating residual tumors following incomplete PTT.

HE-Mind: A model for automatically predicting hematoma expansion after spontaneous intracerebral hemorrhage.

PURPOSE: To develop and validate an end-to-end model for automatically predicting hematoma expansion (HE) after spontaneous intracerebral hemorrhage (sICH) using a novel deep learning framework. METHODS: This multicenter retrospective study collected cranial noncontrast computed tomography (NCCT) images of 490 patients with sICH at admission for model training (n = 236), internal testing (n = 60), and external testing (n = 194). A HE-Mind model was designed to predict HE, which consists of a densely connected U-net for segmentation process, a multi-instance learning strategy for resolving label ambiguity and a Siamese network for classification process. Two radiomics models based on support vector machine or logistic regression and two deep learning models based on residual network or Swin transformer were developed for performance comparison. Reader experiments including physician diagnosis mode and artificial intelligence mode were conducted for efficiency comparison. RESULTS: The HE-Mind model showed better performance compared to the comparative models in predicting HE, with areas under the curve of 0.849 and 0.809 in the internal and external test sets respectively. With the assistance of the HE-Mind model, the predictive accuracy and work efficiency of the emergency physician, junior radiologist, and senior radiologist were significantly improved, with accuracies of 0.768, 0.789, and 0.809 respectively, and reporting times of 7.26 s, 5.08 s, and 3.99 s respectively. CONCLUSIONS: The HE-Mind model could rapidly and automatically process the NCCT data and predict HE after sICH within three seconds, indicating its potential to assist physicians in the clinical diagnosis workflow of HE.

Swirl sign score system: a novel and practical tool for predicting hematoma expansion risk after spontaneous intracerebral haemorrhage.

OBJECTIVE: To methodically analyse the swirl sign and construct a scoring system to predict the risk of hematoma expansion (HE) after spontaneous intracerebral haemorrhage (sICH). METHODS: We analysed 231 of 683 sICH patients with swirl signs on baseline noncontrast CT (NCCT) images. The characteristics of the swirl sign were analysed, including the number, maximum diameter, shape, boundary, minimum CT value of the swirl sign, and the minimum distance from the swirl sign to the edge of the hematoma. In the development cohort, univariate and multivariate analyses were used to identify independent predictors of HE, and logistic regression analysis was used to construct the swirl sign score system. The swirl sign score system was verified in the validation cohort. RESULTS: The number and the minimum CT value of the swirl sign were independent predictors of HE. The swirl sign score system was constructed (2 points for the number of swirl signs >1 and 1 point for the minimum CT value ≤41 Hounsfield units). The area under the curve of the swirl sign score system in predicting HE was 0.773 and 0.770 in the development and validation groups, respectively. CONCLUSIONS: The swirl sign score system is an easy-to-use radiological grading scale that requires only baseline NCCT images to effectively identify subjects at high risk of HE. ADVANCES IN KNOWLEDGE: Our newly developed semiquantitative swirl sign score system greatly improves the ability of swirl sign to predict HE.

High-resolution vessel wall imaging for quantitatively and qualitatively evaluating in-stent stenosis of intracranial aneurysms.

Background: It is critical to accurately and noninvasively evaluate the stented parent artery of intracranial aneurysms (IAs) with endovascular treatment. Objective: To investigate high-resolution vessel wall imaging (HR-VWI) for quantitative and qualitative evaluation of in-stent stenosis (ISS) in IAs treated with stent placement (SP). Methods: Fifty-five patients (58 aneurysms) underwent HR-VWI, contrast-enhanced (CE)-HR-VWI, CE-MR angiography (MRA), time-of-flight (TOF)-MRA, and digital subtraction angiography (DSA) six months after SP, and the reliability of quantitative stent lumen measurements was evaluated by intraclass correlation coefficient (ICC) analysis. Agreement and correlation of quantitative evaluation were estimated by comparing the four MR imaging modalities with DSA. The diagnostic performance for >0%, ≥25%, and ≥50% of ISS degrees and overall diagnostic accuracy for the ISS degrees of the four MR imaging modalities were calculated to qualitative evaluation. Results: The reliability of CE-HR-VWI and HR-VWI for ISS quantitative measurements was excellent (ICC 0.955-0.989). The agreement and correlation of CE-HR-VWI, HR-VWI versus DSA for ISS quantitative measurements were better than those of CE-MRA and TOF-MRA (p < 0.05). The diagnostic performance for distinguishing the degree of ISS >0%, ≥25%, and ≥50% by CE-HR-VWI and HR-VWI was superior to CE-MRA and TOF-MRA, and their overall diagnostic accuracy was 96.55 and 94.83%, respectively. HR-VWI and CE-HR-VWI were not statistically significant in the quantitative and qualitative evaluation of ISS performance (p > 0.05). Conclusion: HR-VWI and CE-HR-VWI have similar performance and value in the quantitative and qualitative evaluation of ISS, and HR-VWI without contrast media could be used as an ideal long-term follow-up approach after SP treatment for IAs.

The relationship between perihematomal edema and hematoma expansion in acute spontaneous intracerebral hemorrhage: an exploratory radiomics analysis study.

Background: The relationship between early perihematomal edema (PHE) and hematoma expansion (HE) is unclear. We investigated this relationship in patients with acute spontaneous intracerebral hemorrhage (ICH), using radiomics. Methods: In this multicenter retrospective study, we analyzed 490 patients with spontaneous ICH who underwent non-contrast computed tomography within 6 h of symptom onset, with follow-up imaging at 24 h. We performed HE and PHE image segmentation, and feature extraction and selection to identify HE-associated optimal radiomics features. We calculated radiomics scores of hematoma (Radscores_HEA) and PHE (Radscores_PHE) and constructed a combined model (Radscore_HEA_PHE). Relationships of the PHE radiomics features or Radscores_PHE with clinical variables, hematoma imaging signs, Radscores_HEA, and HE were assessed by univariate, correlation, and multivariate analyses. We compared predictive performances in the training (n = 296) and validation (n = 194) cohorts. Results: Shape_VoxelVolume and Shape_MinorAxisLength of PHE were identified as optimal radiomics features associated with HE. Radscore_PHE (odds ratio = 1.039, p = 0.032) was an independent HE risk factor after adjusting for the ICH onset time, Glasgow Coma Scale score, baseline hematoma volume, hematoma shape, hematoma density, midline shift, and Radscore_HEA. The areas under the receiver operating characteristic curve of Radscore_PHE in the training and validation cohorts were 0.808 and 0.739, respectively. After incorporating Radscore_PHE, the integrated discrimination improvements of Radscore_HEA_PHE in the training and validation cohorts were 0.009 (p = 0.086) and -0.011 (p < 0.001), respectively. Conclusion: Radscore_PHE, based on Shape_VoxelVolume and Shape_MinorAxisLength of PHE, independently predicts HE, while Radscore_PHE did not add significant incremental value to Radscore_HEA.

A Comparative Study of AI-Based Automated and Manual Postprocessing of Head and Neck CT Angiography: An Independent External Validation with Multi-Vendor and Multi-Center Data.

PURPOSE: To externally validate the performance of automated postprocessing (AP) on head and neck CT Angiography (CTA) and compare it with manual postprocessing (MP). METHODS: This retrospective study included head and neck CTA-exams of patients from three tertiary hospitals acquired on CT scanners from five manufacturers. AP was performed by CerebralDoc. The image quality was assessed using Likert scales, and the qualitative and quantitative diagnostic performance of arterial stenosis and aneurysm, postprocessing time, and scanning radiation dose were also evaluated. RESULTS: A total of 250 patients were included. Among these, 55 patients exhibited significant stenosis (≥ 50%), and 33 patients had aneurysms, diagnosed using original CTA datasets and corresponding multiplanar reconstructions as the reference. While the scores of the V4 segment and the edge of the M1 segment on volume rendering (VR), as well as the C4 segment on maximum intensity projection (MIP), were significantly lower with AP compared to MP across vendors (all P < 0.05), most scores in AP demonstrated image quality that was either superior to or comparable with that of MP. Furthermore, the diagnostic performance of AP was either superior to or comparable with that of MP. Moreover, AP also exhibited advantages in terms of postprocessing time and radiation dose when compared to MP (P < 0.001). CONCLUSION: The AP of CerebralDoc presents clear advantages over MP and holds significant clinical value. However, further optimization is required in the image quality of the V4 and M1 segments on VR as well as the C4 segment on MIP.

NIR-responsive copper nanoliposome composites for cascaded ferrotherapy via ferroptosis actived ICD and IFN-γ released.

Metallic biomaterials activate tumor ferroptosis by increasing oxidative stress, but their efficacy is severely limited in tumor microenvironment. Although interferon gamma (IFN-γ) can promote tumor ferroptosis sensitivity by inhibiting the antioxidant system and promoting lipid accumulation, this effect limited by the lack of IFN-γ accumulation in tumors. Herein, we report a near-infrared (NIR)-responsive HCuS nanocomposite (HCuS-PE@TSL-tlyp-1) that can stimulate immunogenic cell death (ICD)-mediated IFN-γ secretion through exogenous oxidative stress, thereby achieving cascaded ferrotherapy by mutually reinforcing ferroptosis and systemic immunity. Upon laser irradiation, the dissolution of the thermal coating, and the introduction of Cu ions and piperazine-erastin (PE) simultaneously induce oxidative stress by reactive oxygen species (ROS)/lipid peroxide (LPO) accumulation and deplete cystine-glutamate transporter (xCT)/GSH. The onset of oxidative stress-mediated ferroptosis is thus achieved, and ICD is triggered, significantly promoting cytotoxic T-cell (CTL) infiltration for IFN-γ secretion. Furthermore, IFN-γ induces immunogenic tumor ferroptosis by inhibiting xCT-antioxidant pathways and enhancing the ACSL4-fatty acid recruitment pathway, which further promotes sensitivity to ferroptosis in cells. These HCuS nanocomposites combined with aPD-L1 effectively in inhibiting tumor metastasis and recurrence. Importantly, these cascade ferrotherapy results broadens the application of HCuS biomaterials.

Total sleep deprivation alters spontaneous brain activity in medical staff during routine clinical work: a resting-state functional MR imaging study.

Objectives: To assess the effect of total sleep deprivation (TSD) on spontaneous brain activity in medical staff during routine clinical practice. Methods: A total of 36 medical staff members underwent resting-state functional MRI (rs-fMRI) scans and neuropsychological tests twice, corresponding to rested wakefulness (RW) after normal sleep and 24 h of acute TSD. The rs-fMRI features, including the mean fractional amplitude of low-frequency fluctuation (mfALFF), z-score transformed regional homogeneity (zReHo), and functional connectivity (zFC), were compared between RW and TSD. Correlation coefficients between the change in altered rs-fMRI features and the change in altered scores of neuropsychological tests after TSD were calculated. Receiver operating characteristic (ROC) and logistic regression analyses were performed to evaluate the diagnostic efficacy of significantly altered rs-fMRI features in distinguishing between RW and TSD states. Results: Brain regions, including right superior temporal gyrus, bilateral postcentral gyrus, left medial superior frontal gyrus, left middle temporal gyrus, right precentral gyrus, and left precuneus, showed significantly enhanced rs-fMRI features (mfALFF, zReHo, zFC) after TSD. Moreover, the changes in altered rs-fMRI features of the right superior temporal gyrus, bilateral postcentral gyrus, left middle temporal gyrus, and left precuneus were significantly correlated with the changes in several altered scores of neuropsychological tests. The combination of mfALFF (bilateral postcentral gyrus) and zFC (left medial superior frontal gyrus and left precuneus) showed the highest area under the curve (0.870) in distinguishing RW from TSD. Conclusion: Spontaneous brain activity alterations occurred after TSD in routine clinical practice, which might explain the reduced performances of these participants in neurocognitive tests after TSD. These alterations might be potential imaging biomarkers for assessing the impact of TSD and distinguishing between RW and TSD states.

Smart responsive Fe/Mn nanovaccine triggers liver cancer immunotherapy via pyroptosis and pyroptosis-boosted cGAS-STING activation.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) remains suboptimal, characterized by high recurrence and metastasis rates. Although metalloimmunotherapy has shown potential in combating tumor proliferation, recurrence and metastasis, current apoptosis-based metalloimmunotherapy fails to elicit sufficient immune response for HCC. RESULTS: A smart responsive bimetallic nanovaccine was constructed to induce immunogenic cell death (ICD) through pyroptosis and enhance the efficacy of the cGAS-STING pathway. The nanovaccine was composed of manganese-doped mesoporous silica as a carrier, loaded with sorafenib (SOR) and modified with MIL-100 (Fe), where Fe3+, SOR, and Mn2+ were synchronized and released into the tumor with the help of the tumor microenvironment (TME). Afterward, Fe3+ worked synergistically with SOR-induced immunogenic pyroptosis (via both the classical and nonclassical signaling pathways), causing the outflow of abundant immunogenic factors, which contributes to dendritic cell (DC) maturation, and the exposure of double-stranded DNA (dsDNA). Subsequently, the exposed dsDNA and Mn2+ jointly activated the cGAS-STING pathway and induced the release of type I interferons, which further led to DC maturation. Moreover, Mn2+-related T1 magnetic resonance imaging (MRI) was used to visually evaluate the smart response functionality of the nanovaccine. CONCLUSION: The utilization of metallic nanovaccines to induce pyroptosis-mediated immune activation provides a promising paradigm for HCC treatment.

Prediction of microvascular invasion and pathological differentiation of hepatocellular carcinoma based on a deep learning model.

PURPOSE: To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomography (CECT) images to predict microvascular invasion (MVI) and pathological differentiation of hepatocellular carcinoma (HCC). METHODS: This retrospective study included 640 consecutive patients who underwent surgical resection and were pathologically diagnosed with HCC at two medical institutions from April 2017 to May 2022. CECT images and relevant clinical parameters were collected. All the data were divided into 368 training sets, 138 test sets and 134 validation sets. Through DL, a segmentation model was used to obtain a region of interest (ROI) of the liver, and a classification model was established to predict the pathological status of HCC. RESULTS: The liver segmentation model based on the 3D U-Network had a mean intersection over union (mIoU) score of 0.9120 and a Dice score of 0.9473. Among all the classification prediction models based on the Swin transformer, the fusion models combining image information and clinical parameters exhibited the best performance. The area under the curve (AUC) of the fusion model for predicting the MVI status was 0.941, its accuracy was 0.917, and its specificity was 0.908. The AUC values of the fusion model for predicting poorly differentiated, moderately differentiated and highly differentiated HCC based on the test set were 0.962, 0.957 and 0.996, respectively. CONCLUSION: The established DL models established can be used to noninvasively and effectively predict the MVI status and the degree of pathological differentiation of HCC, and aid in clinical diagnosis and treatment.

Diagnostic Accuracy of Liver and Spleen Stiffness in Magnetic Resonance Elastography for the Detection of Gastroesophageal Varices: A Systematic Review and Meta-Analysis.

BACKGROUND: The aim of this meta-analysis was to assess the performance of magnetic resonance elastography (MRE) in detecting gastroesophageal varices (GEV) in patients with chronic liver disease (CLD). METHODS: A literature search in English and Chinese databases such as PubMed, EMBASE, Cochrane Library, Web of Science, and China National Knowledge Infrastructure was conducted. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) of the summary receiver-operating characteristic (SROC) curve with a 95% CI were calculated. A quality analysis of the included study was conducted using the QUADAS-2 tool, and a meta-analysis was performed using Stata16. The clinical practical value of MRE in detecting GEV was evaluated using the Fagan plot. Heterogeneity across studies was explored through meta-regression and subgroup analyses. RESULTS: A total of nine relevant articles that compared liver stiffness (LS) or spleen stiffness (SS) using MRE with esophagogastroduodenoscopy (EGD) to detect the existence of GEV were identified. The pooled summary sensitivity, specificity, PLR, NLR, and DOR of LS or SS for the detection of GEV were 81% (95% CI: 74%, 87%), 72% (95% CI: 62%, 80%), 2.89 (95% CI: 2.12, 3.94), 0.26 (95% CI: 0.19, 0.36), and 10.91 (95% CI: 6.53, 18.24), respectively. The year of publication, study design, and MR equipment are the sources of heterogeneity. There was no significant difference in the publication bias (p > 0.05). CONCLUSIONS: Based on these findings, MRE demonstrates good diagnostic accuracy for detecting GEV in patients with CLD.

The MR Imaging of Primary Intrahepatic Lymphoepithelioma-like Cholangiocarcinoma: A Diagnostic Challenge.

PURPOSE: To characterize the magnetic resonance imaging features of primary intrahepatic lymphoepithelioma-like cholangiocarcinoma (LELCC). MATERIALS AND METHODS: Thirty-four patients with 38 histologically confirmed LELCCs were enrolled retrospectively from January 2014 to August 2022. We evaluated the clinical features, histologic findings, and imaging manifestations on dynamic enhanced MRI. RESULTS: 74% (25/34) of the cases were associated with EBV infection. Moreover, patients infected with EBV exhibited a lower level of Ki-67 proliferation. The serum CA199 level was elevated in 10 patients. The median tumor diameter was 2.8 cm (range, 1.1-8.7 cm). Most tumors were well-defined with a smooth or lobulated margin and showed peripheral hyperintensity and central hypointensity on T2-weighted imaging (T2WI). T2 hyperintense foci were recognized in 8 patients. In the dynamic enhanced MRI, 21 tumors demonstrated Type A enhancement pattern (rim enhancement), 10 demonstrated Type B (rapid wash-in and wash-out), and seven demonstrated Type C (rapid wash-in without wash-out). Capsular enhancement in PVP or DP was found in 22 tumors. A few patients had satellite lesions, portal vein thrombosis, bile duct dilatation, and distal metastasis. Lymph node metastases were discovered pathologically in 11 patients. CONCLUSIONS: MRI findings of LELCC vary and are non-specific. While a majority of LELCCs exhibit typical features of intrahepatic cholangiocarcinoma (iCCA), unique findings like T2 hyperintense foci or capsular enhancement could suggest LELCC. EBV infection and elevated tumor markers can aid in differentiation. However, given the mimics of some cases of liver hypervascular lesions, histological examination remains essential for definitive diagnosis.

Performance of deep learning-based autodetection of arterial stenosis on head and neck CT angiography: an independent external validation study.

PURPOSE: To externally validate the performance of automated stenosis detection on head and neck CT angiography (CTA) and investigate the impact factors using an independent bi-center dataset with digital subtraction angiography (DSA) as the ground truth. MATERIAL AND METHODS: Patients who underwent head and neck CTA and DSA between January 2019 and December 2021 were retrospectively included. The degree of stenosis was automatically evaluated using CerebralDoc based on CTA. The performance of CerebralDoc across levels (per-patient, per-region, per-vessel, and per-segment) and thresholds (≥ 50%, ≥ 70%, and = 100%) was evaluated. Logistic regression was performed to identify independent factors associated with false negative results. RESULTS: 296 patients were analyzed. Specificity across levels and thresholds was high, exceeding 92%. The area under the curve ranged from poor (0.615, 95% CI: 0.544, 0.686; at the region-based analysis for stenosis ≥ 70%) to excellent (0.945, 95% CI: 0.905, 0.985; at the patient-based analysis for stenosis ≥ 50%). Sensitivity ranged from 0.714 (95% CI: 0.675, 0.750) at the segment-based analysis for stenosis ≥ 70% to 0.895 (95% CI: 0.849, 0.919) at the patient-based analysis for stenosis ≥ 50%. The multiple logistic regression analysis revealed that false negative results were primarily more likely to specific stenosis locations (particularly the M2 segment and skull base segment of the internal carotid artery) and occlusion. CONCLUSIONS: CerebralDoc has the potential to automated stenosis detection on head and neck CTA, but further efforts are needed to optimize its performance.

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT. METHODS: This retrospective study included 1049 patients with 1082 lesions from two independent hospitals that were pathologically confirmed as HCC or non-HCC. All patients underwent a four-phase CT imaging protocol. All lesions were graded (LR 4/5/M) by radiologists and divided into an internal (n = 886) and external cohort (n = 196) based on the examination date. In the internal cohort, Swin-Transformer based on different CT protocols were trained and tested for their ability to LI-RADS grading and distinguish HCC from non-HCC, and then validated in the external cohort. We further developed a combined model with the optimal protocol and clinical information for distinguishing HCC from non-HCC. RESULTS: In the test and external validation cohorts, the three-phase protocol without pre-contrast showed κ values of 0.6094 and 0.4845 for LI-RADS grading, and its accuracy was 0.8371 and 0.8061, while the accuracy of the radiologist was 0.8596 and 0.8622, respectively. The AUCs in distinguishing HCC from non-HCC were 0.865 and 0.715 in the test and external validation cohorts, while those of the combined model were 0.887 and 0.808. CONCLUSION: The Swin-Transformer based on three-phase CT protocol without pre-contrast could feasibly simplify LI-RADS grading and distinguish HCC from non-HCC. Furthermore, the DL model have the potential in accurately distinguishing HCC from non-HCC using imaging and highly characteristic clinical data as inputs. CLINICAL RELEVANCE STATEMENT: The application of deep learning model for multiphase CT has proven to improve the clinical applicability of the Liver Imaging Reporting and Data System and provide support to optimize the management of patients with liver diseases. KEY POINTS: • Deep learning (DL) simplifies LI-RADS grading and helps distinguish hepatocellular carcinoma (HCC) from non-HCC. • The Swin-Transformer based on the three-phase CT protocol without pre-contrast outperformed other CT protocols. • The Swin-Transformer provide help in distinguishing HCC from non-HCC by using CT and characteristic clinical information as inputs.

Magnetic Response Combined with Bioactive Ion Therapy: A RONS-Scavenging Theranostic Nanoplatform for Thrombolysis and Renal Ischemia-Reperfusion Injury.

Currently, the limited efficacy of antithrombotic treatments is attributed to the inadequacy of pure drugs and the low ability of drugs to target the thrombus site. More importantly, timely thrombolysis is essential to reduce the sequelae of cardiovascular disease, but ischemia-reperfusion injury (IRI) remains a major challenge that must be solved after blood flow recovery. Herein, a multifunctional therapeutic nanoparticle (NP) based on Fe3O4 and strontium ions encapsulated in mesoporous polydopamine was successfully constructed and then loaded with TNK-tPA (FeM@Sr-TNK NPs). The NPs (59.9 min) significantly prolonged the half-life of thrombolytic drugs, which was 3.04 times that of TNK (19.7 min), and they had good biological safety. The NPs were shown to pass through vascular models with different inner diameters, curvatures, and stenosis under magnetic targeting and to enable accurate diagnosis of thrombi by photoacoustic imaging. NPs combined with the magnetic hyperthermia technique were used to accelerate thrombolysis and quickly open blocked blood vessels. Then, renal IRI-induced functional metabolic disorder and tissue damage were evidently attenuated by scavenging toxic reactive oxygen and nitrogen species and through the protective effects of bioactive ion therapy, including reduced apoptosis, increased angiogenesis, and inhibited fibrosis. In brief, we constructed a multifunctional nanoplatform for integrating a "diagnosis-therapy-protection" approach to achieve comprehensive management from thrombus to renal IRI, promoting the advancement of related technologies.

Evaluation of Preoperative Microvascular Invasion in Hepatocellular Carcinoma Through Multidimensional Parameter Combination Modeling Based on Gd-EOB-DTPA MRI.

Background and Aims: The study established and compared the efficacy of the clinicoradiological model, radiomics model and clinicoradiological-radiomics hybrid model in predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using gadolinium ethoxybenzyl diethylene triaminepentaacetic acid (Gd-EOB-DTPA) enhanced MRI. Methods: This was a study that enrolled 602 HCC patients from two institutions. Least absolute shrinkage and selection operator (Lasso) method was used to screen for the most important clinicoradiological and radiomics features that predict MVI pre-operatively. Three machine learning algorithms were used to establish the clinicoradiological, radiomics, and clinicoradiological-radiomics hybrid models. Area under the curve (AUC) of receiver operating characteristic (ROC) curves and Delong's test were used to compare and quantify the predictive performance of the models. Results: The AUCs of the clinicoradiological model in training and validation cohorts were 0.793 and 0.701, respectively. The radiomics signature of arterial phase (AP) images alone achieved satisfying predictive efficacy for MVI, with AUCs of 0.671 and 0.643 in training and validation cohort, respectively. The combination of clinicoradiological factors and fusion radiomics signature of AP and VP images achieved AUCs of 0.824 and 0.801 in training and validation cohorts, 0.812 and 0.805 in prospective validation and external validation cohorts, respectively. The hybrid model provided the best prediction results. The results of the Delong test revealed that there were statistically significant differences among the clinicoradiological-radiomics hybrid model, clinicoradiological model, and radiomics model (p<0.05). Conclusions: The combination of clinicoradiological factors and fusion radiomics signature of AP and VP images based on Gd-EOB-DTPA-enhanced MRI can effectively predict MVI.

A Synergistic and Efficient Thrombolytic Nanoplatform: A Mechanical Method of Blasting Combined with Thrombolytic Drugs.

Background and Objective: Thrombosis is a common disease that poses a great threat to life and health. Most thrombolytic effects of traditional treatments or nanomedicine are not efficient or safe enough. Therefore, we designed a nanoparticle (NP) with a combination of a phase transition material and thrombolytic drugs for efficient and safe thrombolysis. Methods: A thrombus fibrin-targeted and phase transition NP was designed and contained perfluorohexane (PFH) and the thrombolytic drug rtPA core, with CREKA polypeptides attached to the shell of the PLGA NPs. Characterization of the phase transition and ultrasound imaging of the NPs was carried out under low-intensity focused ultrasound (LIFU). LIFU-responsive drug release in vitro was also explored. Under the synergistic effect of PFH and rtPA, the efficient thrombolysis ability of the NPs was studied in vitro and in vivo. In vivo monitoring of thrombosis and biosafety were also verified. Results: The PPrC NPs had good ultrasound imaging ability under LIFU irradiation and were related to the phase transition characteristics of the NPs. CREKA polypeptides can effectively increase the aggregation of the NPs on thrombi. Under static and dynamic conditions in vitro, the "liquid to gas" transformation effect of PFH can perform the destruction function of the excavator at the thrombus site and promote the specific release of rtPA, and the subsequent rtPA drug thrombolysis can further fully dissolve the thrombus. In vivo experiments showed that the NPs can monitor the formation of thrombi and have good thrombolytic effects, with significantly reduced bleeding side effects. The biochemical indexes of the rats were within normal limits after treatment. Conclusion: PPrC NPs loaded with PFH and rtPA combining a mechanical way of blasting with thrombolytic drugs may be a promising new and reliable approach for thrombus monitoring and treatment.

A theranostic metallodrug modulates immunovascular crosstalk to combat immunosuppressive liver cancer.

Hepatocellular carcinoma (HCC) is a highly malignant, fatal disease with a complex tumor microenvironment (TME) characterized by severe immunosuppression and malformed vascular structures, thus most advanced HCC patients do not respond well to current mainstream pharmacotherapy and T-cell-related immunotherapy. Therefore, an efficient immunovascular crosstalk modulation strategy may help combat HCC by reversing immunosuppression and vessel normalization, especially by reprogramming tumor associated macrophages (TAMs). In this study, tyrosine kinase inhibitor lenvatinib (Len) was loaded into mesoporous Fe3O4 (mFe) nanoparticles (NPs), and bovine serum albumin (BSA) was attached to the NP surface to produce a metallodrug (BSA-mFe@Len NPs). In acidic TME, BSA allowed pH-responsive Len release and mFe exposure. Len directly triggered HCC apoptosis and changed the abnormal TME via vessel normalization, cytotoxic T-lymphocyte recruitment, and regulatory T-cell elimination at tailored dosages. After TAM phagocytosis, mFe NPs reprogrammed TAMs into M1 phenotypes to synergistically amplify antitumor immunity. The metallodrug achieved significant tumor growth inhibition, induced tumor vessel normalization effects, and acquired instant antitumor immunity as well as long-term immune memory in vivo. Furthermore, it displayed good T2 weighted magnetic resonance imaging performance, indicating potential theranostic applications. Collectively, this research provides new insights for unleashing the multifaceted potential of current pharmaceuticals in synergy with metallic nanomedicine for treating intractable liver cancer. STATEMENT OF SIGNIFICANCE: Current pharmacotherapy and immunotherapy have limited success in treating advanced hepatocellular carcinoma (HCC) due to its complex tumor microenvironment (TME). Hence, this work first put forward a theranostic metallodrug by loading lenvatinib (Len) into mesoporous Fe3O4 (mFe) nanoparticles (NPs) and coating a pH-degradable bovine serum albumin corona onto the surface. The metallodrug was able to modulate immunovascular TME for combating HCC via metalloimmunotherapy induced by the mFe NPs and Len's multiple functions (direct triggering of tumor apoptosis, vessel normalization, cytotoxic T-lymphocyte recruitment, and regulatory T-cell elimination). In vivo experiments showed that the metallodrug could significantly inhibit HCC growth and evoke long-term antitumor immune memory, paving a new avenue for treating advanced HCC patients.

Magnetic Nanodroplets for Enhanced Deep Penetration of Solid Tumors and Simultaneous Magnetothermal-Sensitized Immunotherapy against Tumor Proliferation and Metastasis.

The central cells of solid tumors are more proliferative and metastatic than the marginal cells. Therefore, more intelligent strategies for targeting cells with deep spatial distributions in solid tumors remain to be explored. In this work, a biocompatible nanotheranostic agent with a lipid membrane-coated, Fe3 O4 and perfluoropentane (PFP)-loaded, cRGD peptide (specifically targeting the integrin αvß3 receptor)-grafted, magnetic nanodroplets (MNDs) is developed. The MNDs exhibit excellent magnetothermal conversion and controllable magnetic hyperthermia (MHT) through alternating magnetic field regulation. Furthermore, MHT-mediated magnetic droplet vaporization (MDV) induces the expansion of the MNDs to transform them into ultrasonic microbubbles, increasing the permeability of tissue and the cell membrane via the ultrasound-targeted microbubble destruction (UTMD) technique and thereby promoting the deep penetration of MNDs in solid tumors. More importantly, MHT not only causes apoptotic damage by downregulating the expression of the HSP70, cyclin D1, and Bcl-2 proteins in tumor cells but also improves the response rate to T-cell-related immunotherapy by upregulating PD-L1 expression in tumor cells, thus inhibiting the growth of both primary and metastatic tumors. Overall, this work introduces a distinct application of nanoultrasonic biomedicine in cancer therapy and provides an attractive immunotherapy strategy for preventing the proliferation and metastasis of deeply distributed cells in solid tumors.

Preoperative estimation of the survival of patients with unresectable hepatocellular carcinoma achieving complete response after conventional transcatheter arterial chemoembolization: assessments of clinical and LI-RADS MR features.

PURPOSE: To identify the associations of clinical and magnetic resonance (MR) features with overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) achieving complete response (CR) after conventional transcatheter arterial chemoembolization (TACE) and to further develop an individual nomograph to estimate the survival probability. MATERIALS AND METHODS: A total of 112 patients with unresectable HCC treated with TACE as first-line treatment were retrospectively evaluated. Potential risk factors associated with OS were identified by univariate and multivariate Cox analyses. The survival model was developed by multivariate Cox proportional hazard model. The area under the receiver operating characteristic curve was calculated to assess the performance of each marker and of the whole model. Discrimination was performed using Kaplan-Meier curves, and the survival curves were compared by the log-rank test. A nomogram derived from the survival model was established. RESULTS: Multivariate Cox analyses indicated that nonsmooth tumor margin, peritumoral enhancement, fat sparing in solid mass, and Barcelona clinic liver cancer (BCLC) stage were independent risk indicators associated with OS. The survival model showed acceptable diagnostic power, with an area under the curve (AUC) of 0.687. Kaplan-Meier curves demonstrated that the model discriminated well, as the high-risk and low-risk groups had median survival times of 21.6 months and 34.8 months, respectively (log-rank test, P = 0.01). CONCLUSIONS: Nonsmooth tumor margin, peritumoral enhancement, fat sparing in solid mass, and BCLC stage were potential biomarkers to evaluate the survival with favorable performance and discriminate HCC patients with CR under conventional TACE treatment.