Cationic nanoparticle as an inhibitor of cell-free DNA-induced inflammation

Cell-free DNA (cfDNA) released from damaged or dead cells can activate DNA sensors that exacerbate the pathogenesis of rheumatoid arthritis (RA). Here we show that ~40 nm cationic nanoparticles (cNP) can scavenge cfDNA derived from RA patients and inhibit the activation of primary synovial fluid monocytes and fibroblast-like synoviocytes. Using clinical scoring, micro-CT images, MRI, and histology, we show that intravenous injection of cNP into a CpG-induced mouse model or collagen-induced arthritis rat model can relieve RA symptoms including ankle and tissue swelling, and bone and cartilage damage. This culminates in the manifestation of partial mobility recovery of the treated rats in a rotational cage test. Mechanistic studies on intracellular trafficking and biodistribution of cNP, as well as measurement of cytokine expression in the joints and cfDNA levels in systemic circulation and inflamed joints also correlate with therapeutic outcomes. This work suggests a new direction of nanomedicine in treating inflammatory diseases.

A Review of Resveratrol as a Potent Chemoprotective and Synergistic Agent in Cancer Chemotherapy

Background: Cancer has become a major disease endangering human health around the world. Conventional chemotherapy suffers from many side effects including pain, cardiotoxicity, hepatotoxicity, and renal toxicity. This review aims to describe a natural product of resveratrol as a chemoprotective and synergistic agent in the modulation of cancer chemotherapy. Methods: The publications were identified by comprehensive searching of SciFinder, PubMed, Web of Science, and our own reference library. Search terms included combinations of "resveratrol," "cancer," "natural products," "chemotherapy," and "side effects." Selection of material focused on resveratrol reducing the side effects on cancer chemotherapy. Results: Thirty one references were referred in this review to outline resveratrol as a potent chemoprotective and synergistic agent in cancer chemotherapy, including 22 papers for describing the chemoprotective effects, and 9 papers for illustrating the synergistic effects. Conclusion: This study provides a systematic summary of resveratrol serving as a potent chemoprotective and synergistic agent to reduce the associated-side effects and enhance the therapeutic outcomes in cancer chemotherapy. Further studies in terms of resveratrol on a large amount of preclinical tests and clinical trials are highly demanded.

Multifunctional Nanoregulator Reshapes Immune Microenvironment and Enhances Immune Memory for Tumor Immunotherapy

Hypoxia leads to up-regulation of PD-L1 and decreases T lymphocyte infiltration, thus boosting immunotherapeutic resistance of tumors. Moreover, tumor-infiltrating myeloid cells such as myeloid-derived suppressor cells (MDSCs) correlate with potent immune suppressive activity and resistance to the immune checkpoint blocking (ICB) in tumor sites. Here, a multifunctional nanoregulator incorporating MnO2 particles and small molecular IPI549 is developed, which can reshape the tumor immune microenvironment (TIME) to unleash the immune system. The intravenously administered nanoregulator effectively accumulates in tumor sites to alleviate hypoxia via oxygen-generating reduction of MnO2 and to inhibit PI3Kγ on MDSCs via IPI549 release in the tumor microenvironment (TME), which results in concurrent downregulation of PD-L1 expression, polarization of tumor associated macrophages (TAMs) toward pro-inflammatory M1-like phenotype (tumor-suppressive), enhanced infiltration of CD4+ helper T lymphocytes (Th cells), and cytotoxic CD8+ T lymphocytes (Tc cells), and suppressed infiltration of regulatory T lymphocytes (Treg cells) for effective tumor immunotherapy. Furthermore, the local generation of Mn2+ in TME allows tumor-specific magnetic resonance imaging (MRI). More excitingly, the nanoregulator-reshaped TIME is effectively reserved due to the synergistic effect of hypoxia alleviation and MDSC PI3Kγ inhibition, leading to remarkable post-medication inhibition of tumor re-growth and metastasis in an animal study.

Theranostic Nanomedicine for Synergistic Chemodynamic Therapy and Chemotherapy of Orthotopic Glioma

Glioma is a common primary brain malignancy with a poor prognosis. Chemotherapy is the first-line treatment for brain tumors but low efficiency of drugs in crossing the blood-brain barrier (BBB) and drug resistance related to tumor hypoxia thwart its efficacy. Herein, a theranostic nanodrug (iRPPA@TMZ/MnO) is developed by incorporating oleic acid-modified manganese oxide (MnO) and temozolomide (TMZ) into a polyethylene glycol-poly(2-(diisopropylamino)ethyl methacrylate-based polymeric micelle containing internalizing arginine-glycine-aspartic acid (iRGD). The presence of iRGD provides the nanodrug with a high capacity of crossing the BBB and penetrating the tumor tissue. After accumulation in glioma, the nanodrug responds to the tumor microenvironment to simultaneously release TMZ, Mn2+, and O2. The released TMZ induces tumor cell apoptosis and the released Mn2+ causes intracellular oxidative stress that kill tumor cells via a Fenton-like reaction. The O2 produced in situ alleviates tumor hypoxia and enhances the chemotherapy/chemodynamic therapeutic effects against glioma. The Mn2+ can also serve as a magnetic resonance imaging (MRI) contrast agent for tumor imaging during therapy. The study demonstrates the great potential of this multifunctional nanodrug for MRI-visible therapy of brain glioma.

Folic acid-functionalized polyethylenimine superparamagnetic iron oxide nanoparticles as theranostic agents for magnetic resonance imaging and PD-L1 siRNA delivery for gastric cancer

Programmed death ligand-1 (PD-L1), which is highly expressed in gastric cancers, interacts with programmed death-1 (PD-1) on T cells and is involved in T-cell immune resistance. To increase the therapeutic safety and accuracy of PD-1/PD-L1 blockade, RNA interference through targeted gene delivery was performed in our study. We developed folic acid (FA)- and disulfide (SS)-polyethylene glycol (PEG)-conjugated polyethylenimine (PEI) complexed with superparamagnetic iron oxide Fe3O4 nanoparticles (SPIONs) as a siRNA-delivery system for PD-L1 knockdown. The characterization, binding ability, cytotoxicity, transfection efficiency, and cellular internalization of the polyplex were determined. At nitrogen:phosphate (N:P) ratios of 10 or above, the FA-PEG-SS-PEI-SPIONs bound to PD-L1 siRNA to form a polyplex with a diameter of approximately 120 nm. Cell-viability assays showed that the polyplex had minimal cytotoxicity at low N:P ratios. The FA-conjugated polyplex showed higher transfection efficiency and cellular internalization in the folate receptor-overexpressing gastric cancer cell line SGC-7901 than a non-FA-conjugated polyplex. Subsequently, we adopted the targeted FA-PEG-SS-PEI-SPION/siRNA polyplexes at an N:P ratio of 10 for function studies. Cellular magnetic resonance imaging (MRI) showed that the polyplex could also act as a T2-weighted contrast agent for cancer MRI. Furthermore, one of four PD-L1 siRNAs exhibited effective PD-L1 knockdown in PD-L1-overexpressing SGC-7901. To determine the effects of the functionalized polyplex on T-cell function, we established a coculture model of activated T cells and SGC-7901 cells and demonstrated changes in secreted cytokines. Our findings highlight the potential of this class of multifunctional theranostic nanoparticles for effective targeted PD-L1-knockdown therapy and MRI diagnosis in gastric cancers.

Nanofibrous nerve guidance conduits decorated with decellularized matrix hydrogel facilitate peripheral nerve injury repair

Rationale: Peripheral nerve injury (PNI) is a great challenge for regenerative medicine. Nerve autograft is the gold standard for clinical PNI repair. Due to its significant drawbacks, artificial nerve guidance conduits (NGCs) have drawn much attention as replacement therapies. We developed a combinatorial NGC consisting of longitudinally aligned electrospun nanofibers and porcine decellularized nerve matrix hydrogel (pDNM gel). The in vivo capacity for facilitating nerve tissue regeneration and functional recovery was evaluated in a rat sciatic nerve defect model. Methods: Poly (L-lactic acid) (PLLA) was electrospun into randomly oriented (PLLA-random) and longitudinally aligned (PLLA-aligned) nanofibers. PLLA-aligned were further coated with pDNM gel at concentrations of 0.25% (PLLA-aligned/0.25% pDNM gel) and 1% (PLLA-aligned/1% pDNM gel). Axonal extension and Schwann cells migration were evaluated by immunofluorescence staining of dorsal root ganglia cultured on the scaffolds. To fabricate implantable NGCs, the nanofibrous scaffolds were rolled and covered with an electrospun protection tube. The fabricated NGCs were then implanted into a 5 mm sciatic nerve defect model in adult male Sprague-Dawley rats. Nerves treated with NGCs were compared to contralateral uninjured nerves (control group), injured but untreated nerves (unstitched group), and autografted nerves. Nerve regeneration was monitored by an established set of assays, including T2 values and diffusion tensor imaging (DTI) derived from multiparametric magnetic resonance imaging (MRI), histological assessments, and immunostaining. Nerve functional recovery was evaluated by walking track analysis. Results: PLLA-aligned/0.25% pDNM gel scaffold exhibited the best performance in facilitating directed axonal extension and Schwann cells migration in vitro due to the combined effects of the topological cues provided by the aligned nanofibers and the biochemical cues retained in the pDNM gel. Consistent results were obtained in animal experiments with the fabricated NGCs. Both the T2 and fractional anisotropy values of the PLLA-aligned/0.25% pDNM gel group were the closest to those of the autografted group, and returned to normal much faster than those of the other NGCs groups. Histological assessment indicated that the implanted PLLA-aligned/0.25% pDNM gel NGC resulted in the largest number of axons and the most extensive myelination among all fabricated NGCs. Further, the PLLA-aligned/0.25% pDNM gel group exhibited the highest sciatic nerve function index, which was comparable to that of the autografted group, at 8 weeks post-surgery. Conclusions: NGCs composed of aligned PLLA nanofibers decorated with 0.25% pDNM gel provided both topological and biochemical guidance for directing and promoting axonal extension, nerve fiber myelination, and functional recovery. Moreover, T2-mapping and DTI metrics were found to be useful non-invasive monitoring techniques for PNI treatment.

Predictive value of pretreatment MRI texture analysis in patients with primary nasopharyngeal carcinoma

OBJECTIVES

To determine the predictive value of pretreatment MRI texture analysis for progression-free survival (PFS) in patients with primary nasopharyngeal carcinoma (NPC).

METHODS

Ethical approval by the institutional review board was obtained for this retrospective analysis. In 79 patients with primary NPC, texture analysis of the primary tumour was performed on pretreatment T2 and contrast-enhanced T1-weighted images (T2WIs and CE-T1WIs). The Cox proportional hazards model was used to determine the association of texture features, tumour volume and the tumour-node-metastasis (TNM) stage with PFS. Survival curves were plotted using the Kaplan-Meier method. The prognostic performance was evaluated with the receiver operating characteristic (ROC) analyses and C-index.

RESULTS

Tumour volume (hazard ratio, 1.054; 95% confidence interval [CI], 1.016-1.093) and CE-T1WI-based uniformity (hazard ratio, 0; 95% CI, 0-0.001) were identified as independent predictors for PFS (p < 0.05). Kaplan-Meier analysis showed that smaller tumour volume (less than the cut-off value, 11.699 cm3) and higher CE-T1WI-based uniformity (greater than the cut-off value, 0.856) were associated with improved PFS (p < 0.05). The combination of CE-T1WI-based uniformity with tumour volume and the overall stage predicted PFS better (area under the curve [AUC], 0.825; Cindex, 0.794) than the tumour volume (AUC, 0.659; C-index, 0.616) or the overall stage (AUC, 0.636; C-index, 0.627) did (p < 0.05).

CONCLUSIONS

A texture parameter of pretreatment CE-T1WI-based uniformity improves the prediction of PFS in NPC patients.

KEY POINTS

• Higher CE-T1WI-based uniformity and smaller tumour volume are predictive of improved PFS in NPC patients. • The combination of CE-T1WI-based uniformity with tumour volume and the overall stage has a better predictive ability for PFS than the tumour volume or the overall stage alone. • Pretreatment MRI texture analysis has a prognostic value for NPC patients.

Deep Learning-Based Radiomics of B-Mode Ultrasonography and Shear-Wave Elastography: Improved Performance in Breast Mass Classification

OBJECTIVE

Shear-wave elastography (SWE) can improve the diagnostic specificity of the B-model ultrasonography (US) in breast cancer. However, whether deep learning-based radiomics signatures based on the B-mode US (B-US-RS) or SWE (SWE-RS) could further improve the diagnostic performance remains to be investigated. We aimed to develop the B-US-RS and SWE-RS and determine their performances in classifying breast masses.

MATERIALS AND METHODS

This retrospective study included 291 women (mean age ± standard deviation, 40.9 ± 12.3 years) from two centers who had US-visible solid breast masses and underwent biopsy and/or surgical resection between June 2015 and July 2017. B-mode US and SWE images of the 198 masses in 198 patients (training cohort) from center 1 were segmented, respectively, to construct B-US-RS and SWE-RS using the least absolute shrinkage and selection operator regression and tested in an independent validation cohort of 65 masses in 65 patients from center 1 and in an external validation cohort of 28 masses in 28 patients from center 2. The performances of B-US-RS and SWE-RS were assessed using receiver operating characteristic (ROC) analysis and compared with that of radiologist assessment [Breast Imaging Reporting and Data System (BI-RADS)] and quantitative SWE parameters [maximum elasticity (E max), mean elasticity (E mean), elasticity ratio (E ratio), and elastic modulus standard deviation (E SD)] by using the McNemar test.

RESULTS

The single best-performing quantitative SWE parameter, E max, had a higher specificity than BI-RADS assessment in the training and independent validation cohorts (P < 0.001 for both). The areas under the ROC curves (AUCs) of B-US-RS and SWE-RS both were 0.99 (95% CI = 0.99-1.00) in the training cohort, 1.00 (95% CI = 1.00-1.00) in the independent validation cohort, and 1.00 (95% CI = 1.00-1.00) in the external validation cohort. The specificities of B-US-RS and SWE-RS were higher than that of E max in the training (P < 0.001 for both) and independent validation cohorts (P = 0.02 for both).

CONCLUSION

The B-US-RS and SWE-RS outperformed the quantitative SWE parameters and BI-RADS assessment for classifying breast masses. The integration of the deep learning-based radiomics approach would help improve the classification ability of B-mode US and SWE for breast masses.

The long-term fate of mesenchymal stem cells labeled with magnetic resonance imaging-visible polymersomes in cerebral ischemia

Understanding the long-term fate and potential mechanisms of mesenchymal stem cells (MSCs) after transplantation is essential for improving functional benefits of stem cell-based stroke treatment. Magnetic resonance imaging (MRI) is considered an attractive and clinically translatable tool for longitudinal tracking of stem cells, but certain controversies have arisen in this regard. In this study, we used SPION-loaded cationic polymersomes to label green fluorescent protein (GFP)-expressing MSCs to determine whether MRI can accurately reflect survival, long-term fate, and potential mechanisms of MSCs in ischemic stroke therapy. Our results showed that MSCs could improve the functional outcome and reduce the infarct volume of stroke in the brain. In vivo MRI can verify the biodistribution and migration of grafted cells when pre-labeled with SPION-loaded polymersome. The dynamic change of low signal volume on MRI can reflect the tendency of cell survival and apoptosis, but may overestimate long-term survival owing to the presence of iron-laden macrophages around cell graft. Only a small fraction of grafted cells survived up to 8 weeks after transplantation. A minority of these surviving cells were differentiated into astrocytes, but not into neurons. MSCs might exert their therapeutic effect via secreting paracrine factors rather than directing cell replacement through differentiation into neuronal and/or glial phenotypes.

Mean Apparent Propagator MRI Is Better Than Conventional Diffusion Tensor Imaging for the Evaluation of Parkinson's Disease: A Prospective Pilot Study

BACKGROUND AND PURPOSE

Mean apparent propagator (MAP) MRI is a novel diffusion imaging method to map tissue microstructure. The purpose of this study was to evaluate the diagnostic value of the MAP MRI in Parkinson's disease (PD) in comparison with conventional diffusion tensor imaging (DTI).

METHODS

23 PD patients and 22 age- and gender-matched healthy controls were included. MAP MRI and DTI were performed on a 3T MR scanner with a 20-channel head coil. The MAP metrics including mean square displacement (MSD), return to the origin probability (RTOP), return to the axis probability (RTAP), and return to the plane probability (RTPP), and DTI metrics including fractional anisotropy (FA), and mean diffusivity (MD), were measured in subcortical gray matter and compared between the two groups. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of all the metrics. The association between the diffusion metrics and disease severity was assessed by Pearson correlation analysis.

RESULTS

For MAP MRI, the mean values of MSD in the bilateral caudate, pallidum, putamen, thalamus and substantia nigra (SN) were higher in PD patients than in healthy controls (p FDR ≤ 0.001); the mean values of the zero displacement probabilities (RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus were lower in PD patients (p FDR < 0.001). For DTI, only FA in the bilateral SN was significantly higher in PD patients than those in the controls (p FDR < 0.001). ROC analysis showed that the areas under the curves of MAP MRI metrics (MSD, RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus (range, 0.85-0.94) were greater than those of FA and MD of DTI (range, 0.55-0.69) in discriminating between PD patients and healthy controls. RTAP in the ipsilateral pallidum (r = -0.56, p FDR = 0.027), RTOP in the bilateral and contralateral putamen (r = -0.58, p FDR = 0.019; r = -0.57, p FDR = 0.024) were negatively correlated with UPDRS III motor scores.

CONCLUSION

MAP MRI outperformed the conventional DTI in the diagnosis of PD and evaluation of the disease severity.

Identification of Specific Joint-Inflammatogenic Cell-Free DNA Molecules From Synovial Fluids of Patients With Rheumatoid Arthritis

Elevated cell-free DNA (cfDNA) levels in the plasma and synovial fluid of rheumatoid arthritis (RA) patients are proposed to be pathologically relevant. However, direct evidence to support this perception is lacking, and molecular feature of the cfDNA molecules with assumed pathological function is not well characterized. Here, we confirm remarkably increased levels of total synovial fluid and plasma cfDNAs in a large cohort of patients with rheumatoid arthritis compared to the counterparts in osteoarthritis, and demonstrate the potent inflammatogenic effects of RA synovial fluid cfDNA on both human monocyte cell line and primary cells related to RA. Massively parallel sequencing identifies distinct molecular pattern of cfDNA in RA, as characterized by enriching CpG-motif containing sequences. Importantly, these identified CpG-motif-rich sequences are hypomethylated in RA patients and induce severe inflammatory responses both in vitro and in vivo. Our data demonstrate the pathological role of global and specific cfDNA molecules in RA, thereby identifying novel therapeutic target candidate and potential biomarker for RA.

Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion-weighted MRI models

BACKGROUND

To compare the diagnostic performance of neurite orientation dispersion and density imaging (NODDI), mean apparent propagator magnetic resonance imaging (MAP-MRI), diffusion kurtosis imaging (DKI), diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) in distinguishing high-grade gliomas (HGGs) from solitary brain metastases (SBMs).

METHODS

Patients with previously untreated, histopathologically confirmed HGGs (n = 20) or SBMs (n = 21) appearing as a solitary and contrast-enhancing lesion on structural MRI were prospectively recruited to undergo diffusion-weighted MRI. DWI data were obtained using a q-space Cartesian grid sampling procedure and were processed to generate parametric maps by fitting the NODDI, MAP-MRI, DKI, DTI and DWI models. The diffusion metrics of the contrast-enhancing tumor and peritumoral edema were measured. Differences in the diffusion metrics were compared between HGGs and SBMs, followed by receiver operating characteristic (ROC) analysis and the Hanley and McNeill test to determine their diagnostic performances.

RESULTS

NODDI-based isotropic volume fraction (Viso) and orientation dispersion index (ODI); MAP-MRI-based mean-squared displacement (MSD) and q-space inverse variance (QIV); DKI-generated radial, mean diffusivity and fractional anisotropy (RDk, MDk and FAk); and DTI-generated radial, mean diffusivity and fractional anisotropy (RD, MD and FA) of the contrast-enhancing tumor were significantly different between HGGs and SBMs (p < 0.05). The best single discriminative parameters of each model were Viso, MSD, RDk and RD for NODDI, MAP-MRI, DKI and DTI, respectively. The AUC of Viso (0.871) was significantly higher than that of MSD (0.736), RDk (0.760) and RD (0.733) (p < 0.05).

CONCLUSION

NODDI outperforms MAP-MRI, DKI, DTI and DWI in differentiating between HGGs and SBMs. NODDI-based Viso has the highest performance.

Superparamagnetic Iron Oxide Nanoparticles-Complexed Cationic Amylose for In Vivo Magnetic Resonance Imaging Tracking of Transplanted Stem Cells in Stroke

Cell-based therapy with mesenchymal stem cells (MSCs) is a promising strategy for acute ischemic stroke. In vivo tracking of therapeutic stem cells with magnetic resonance imaging (MRI) is imperative for better understanding cellular survival and migrational dynamics over time. In this study, we develop a novel biocompatible nanocomplex (ASP-SPIONs) based on cationic amylose, by introducing spermine and the image label, ultrasmall superparamagnetic iron oxide nanoparticles (SPIONs), to label MSCs. The capacity, efficiency, and cytotoxicity of the nanocomplex in transferring SPIONs into green fluorescence protein-modified MSCs were tested; and the performance of in vivo MRI tracking of the transplanted cells in acute ischemic stroke was determined. The results demonstrated that the new class of SPIONs-complexed nanoparticles based on biodegradable amylose can serve as a highly effective and safe carrier to transfer magnetic label into stem cells. A reliable tracking of transplanted stem cells in stroke was achieved by MRI up to 6 weeks, with the desirable therapeutic benefit of stem cells on stroke retained. With the advantages of a relatively low SPIONs concentration and a short labeling period, the biocompatible complex of cationic amylose with SPIONs is highly translatable for clinical application. It holds great promise in efficient, rapid, and safe labeling of stem cells for subsequent cellular MRI tracking in regenerative medicine.

In Vivo Long-Term Tracking of Neural Stem Cells Transplanted into an Acute Ischemic Stroke model with Reporter Gene-Based Bimodal MR and Optical Imaging

Transplantation of neural stem cells (NSCs) is emerging as a new therapeutic approach for stroke. Real-time imaging of transplanted NSCs is essential for successful cell delivery, safety monitoring, tracking cell fate and function, and understanding the interactions of transplanted cells with the host environment. Magnetic resonance imaging (MRI) of magnetic nanoparticle-labeled cells has been the most widely used means to track stem cells in vivo. Nevertheless, it does not allow for the reliable discrimination between live and dead cells. Reporter gene-based MRI was considered as an alternative strategy to overcome this shortcoming. In this work, a class of lentiviral vector-encoding ferritin heavy chain (FTH) and enhanced green fluorescent protein (EGFP) was constructed to deliver reporter genes into NSCs. After these transgenic NSCs were transplanted into the contralateral hemisphere of rats with acute ischemic stroke, MRI and fluorescence imaging (FLI) were performed in vivo for tracking the fate of transplanted cells over a long period of 6 wk. The results demonstrated that the FTH and EGFP can be effectively and safely delivered to NSCs via the designed lentiviral vector. The distribution and migration of grafted stem cells could be monitored by bimodal MRI and FLI. FTH can be used as a robust MRI reporter for reliable reporting of the short-term viability of cell grafts, whereas its capacity for tracking the long-term viability of stem cells remains dependent on several confounding factors such as cell death and the concomitant reactive inflammation.

Magnetic Cationic Amylose Nanoparticles Used to Deliver Survivin-Small Interfering RNA for Gene Therapy of Hepatocellular Carcinoma In Vitro

Amylose is a promising nanocarrier for gene delivery in terms of its good biocompatibility and high transfection efficiency. Small interfering RNA against survivin (survivin-siRNA) can cause tumor apoptosis by silencing a hepatocellular carcinoma (HCC)-specific gene at the messenger RNA level. In this study, we developed a new class of folate-functionalized, superparamagnetic iron oxide (SPIO)-loaded cationic amylose nanoparticles to deliver survivin-siRNA to HCC cells. The cellular uptake of nanocomplexes, cytotoxicity, cell apoptosis, and gene suppression mediated by siRNA-complexed nanoparticles were tested. The results demonstrated that folate-functionalized, SPIO-loaded cationic amylose nanoparticles can mediate a specific and safe cellular uptake of survivin-siRNA with high transfection efficiency, resulting in a robust survivin gene downregulation in HCC cells. The biocompatible complex of cationic amylose could be used as an efficient, rapid, and safe gene delivery vector. Upon SPIO loading, it holds a great promise as a theranostic carrier for gene therapy of HCC.

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND

Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma (HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.

AIM

To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.

METHODS

For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.

RESULTS

Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure (area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure (area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model (integrated discrimination improvement = 0.117, P = 0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic (P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.

CONCLUSION

A radiomics-based model of preoperative gadoxetic acid-enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.

Pretreatment DCE-MRI-Based Deep Learning Outperforms Radiomics Analysis in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

PURPOSE

To compare the performances of deep learning (DL) to radiomics analysis (RA) in predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) based on pretreatment dynamic contrast-enhanced MRI (DCE-MRI) in breast cancer.

MATERIALS AND METHODS

This retrospective study included 356 breast cancer patients who underwent DCE-MRI before NAC and underwent surgery after NAC. Image features and kinetic parameters of tumors were derived from DCE-MRI. Molecular information was assessed based on immunohistochemistry results. The image-based RA and DL models were constructed by adding kinetic parameters or molecular information to image-only linear discriminant analysis (LDA) and convolutional neural network (CNN) models. The predictive performances of developed models were assessed by receiver operating characteristic (ROC) curve analysis and compared with the DeLong method.

RESULTS

The overall pCR rate was 23.3% (83/356). The area under the ROC (AUROC) of the image-kinetic-molecular RA model was 0.781 [95% confidence interval (CI): 0.735, 0.828], which was higher than that of the image-kinetic RA model (0.629, 95% CI: 0.595, 0.663; P < 0.001) and comparable to that of the image-molecular RA model (0.755, 95% CI: 0.708, 0.802; P = 0.133). The AUROC of the image-kinetic-molecular DL model was 0.83 (95% CI: 0.816, 0.847), which was higher than that of the image-kinetic and image-molecular DL models (0.707, 95% CI: 0.654, 0.761; 0.79, 95% CI: 0.768, 0.812; P < 0.001) and higher than that of the image-kinetic-molecular RA model (0.778, 95% CI: 0.735, 0.828; P < 0.001).

CONCLUSIONS

The pretreatment DCE-MRI-based DL model is superior to the RA model in predicting pCR to NAC in breast cancer patients. The image-kinetic-molecular DL model has the best prediction performance.

Aberrant Functional and Causal Connectivity in Acute Tinnitus With Sensorineural Hearing Loss

PURPOSE

The neural bases in acute tinnitus remains largely undetected. The objective of this study was to identify the alteration of the brain network involved in patients with acute tinnitus and hearing loss.

METHODS

Acute tinnitus patients (n = 24) with hearing loss and age-, sex-, education-matched healthy controls (n = 21) participated in the current study and underwent resting-state functional magnetic resonance imaging (fMRI) scanning. Regional homogeneity and amplitude of low-frequency fluctuation were used to investigate the local spontaneous neural activity and functional connectivity (FC), and Granger causality analysis (GCA) was used to analyze the undirected and directed connectivity of brain regions.

RESULTS

Compared with healthy subjects, acute tinnitus patients had a general reduction in FC between auditory and non-auditory brain regions. Based on FC analysis, the superior temporal gyrus (STG) revealed reduced undirected connectivity with non-auditory brain regions including the amygdala (AMYG), nucleus accumbens (NAc), the cerebellum, and postcentral gyrus (PoCG). Using the GCA algorithm, increased effective connectivity from the right AMYG to the right STG, and reduced connectivity from the right PoCG to the left NAc was observed in acute tinnitus patients with hearing loss. The pure-tone threshold was positively correlated with FC between the AMYG and STG, and negatively correlated with FC between the left NAc and the right PoCG. In addition, a negative association between the GCA value from the right PoCG to the left NAc and the THI scores was observed.

CONCLUSION

Acute tinnitus patients have aberrant FC strength and causal connectivity in both the auditory and non-auditory cortex, especially in the STG, AMYG, and NAc. The current findings will provide a new perspective for understanding the neuropathophysiological mechanism in acute tinnitus.

In Vivo Targeted Magnetic Resonance Imaging of Endogenous Neural Stem Cells in the Adult Rodent Brain

Neural stem cells in the adult mammalian brain have a significant level of neurogenesis plasticity. In vivo monitoring of adult endogenous NSCs would be of great benefit to the understanding of the neurogenesis plasticity under normal and pathological conditions. Here we show the feasibility of in vivo targeted MR imaging of endogenous NSCs in adult mouse brain by intraventricular delivery of monoclonal anti-CD15 antibody conjugated superparamagnetic iron oxide nanoparticles. After intraventricular administration of these nanoparticles, the subpopulation of NSCs in the anterior subventricular zone and the beginning of the rostral migratory stream could be in situ labeled and were in vivo visualized with 7.0-T MR imaging during a period from 1 day to 7 days after the injection. Histology confirmed that the injected targeted nanoparticles were specifically bound to CD15 positive cells and their surrounding extracellular matrix. Our results suggest that in vivo targeted MR imaging of endogenous neural stem cells in adult rodent brain could be achieved by using anti-CD15-SPIONs as the molecular probe; and this targeting imaging strategy has the advantage of a rapid in vivo monitoring of the subpopulation of endogenous NSCs in adult brains.

In Vivo Targeted MR Imaging of Endogenous Neural Stem Cells in Ischemic Stroke

Acute ischemic stroke remains a leading cause of death and disability. Endogenous neurogenesis enhanced via activation of neural stem cells (NSCs) could be a promising method for stroke treatment. In vivo targeted tracking is highly desirable for monitoring the dynamics of endogenous NSCs in stroke. Previously, we have successfully realized in vivo targeted MR imaging of endogenous NSCs in normal adult mice brains by using anti-CD15 antibody-conjugated superparamagnetic iron oxide nanoparticles (anti-CD15-SPIONs) as the molecular probe. Herein, we explore the performance of this molecular probe in targeted in vivo tracking of activated endogenous NSCs in ischemic stroke. Our study showed that intraventricular injection of anti-CD15-SPIONs could label activated endogenous NSCs in situ seven days after ischemic stroke, which were detected as enlarged areas of hypo-intense signals on MR imaging at 7.0 T. The treatment of cytosine arabinosine could inhibit the activation of endogenous NSCs, which was featured by the disappearance of areas of hypo-intense signals on MR imaging. Using anti-CD15-SPIONs as imaging probes, the dynamic process of activation of endogenous NSCs could be readily monitored by in vivo MR imaging. This targeted imaging strategy would be of great benefit to develop a new therapeutic strategy utilizing endogenous NSCs for ischemic stroke.

Accurately Discriminating COVID-19 from Viral and Bacterial Pneumonia According to CT Images Via Deep Learning

Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films brings a lot of concentration and time for doctors. Therefore, it is necessary to develop an automatic CT image diagnosis system to assist doctors in diagnosis. Previous studies devoted to COVID-19 in the past months focused mostly on discriminating COVID-19 infected patients from healthy persons and/or bacterial pneumonia patients, and have ignored typical viral pneumonia since it is hard to collect samples for viral pneumonia that is less frequent in adults. In addition, it is much more challenging to discriminate COVID-19 from typical viral pneumonia as COVID-19 is also a kind of virus. In this study, we have collected CT images of 262, 100, 219, and 78 persons for COVID-19, bacterial pneumonia, typical viral pneumonia, and healthy controls, respectively. To the best of our knowledge, this was the first study of quaternary classification to include also typical viral pneumonia. To effectively capture the subtle differences in CT images, we have constructed a new model by combining the ResNet50 backbone with SE blocks that was recently developed for fine image analysis. Our model was shown to outperform commonly used baseline models, achieving an overall accuracy of 0.94 with AUC of 0.96, recall of 0.94, precision of 0.95, and F1-score of 0.94. The model is available in https://github.com/Zhengfudan/COVID-19-Diagnosis-and-Pneumonia-Classification .

CXCL10 and Nrf2-upregulated mesenchymal stem cells reinvigorate T lymphocytes for combating glioblastoma

BACKGROUND

Lack of tumor-infiltrating T lymphocytes and concurrent T-cell dysfunction have been identified as major contributors to glioblastoma (GBM) immunotherapy resistance. Upregulating CXCL10 in the tumor microenvironment (TME) is a promising immunotherapeutic approach that potentially increases tumor-infiltrating T cells and boosts T-cell activity but is lacking effective delivery methods.

METHODS

In this study, mesenchymal stem cells (MSCs) were transduced with a recombinant lentivirus encoding Cxcl10, Nrf2 (an anti-apoptosis gene), and a ferritin heavy chain (Fth) reporter gene in order to increase their CXCL10 secretion, TME survival, and MRI visibility. Using FTH-MRI guidance, these cells were injected into the tumor periphery of orthotopic GL261 and CT2A GBMs in mice. Combination therapy consisting of CXCL10-Nrf2-FTH-MSC transplantation together with immune checkpoint blockade (ICB) was also performed for CT2A GBMs. Thereafter, in vivo and serial MRI, survival analysis, and histology examinations were conducted to assess the treatments' efficacy and mechanism.

RESULTS

CXCL10-Nrf2-FTH-MSCs exhibit enhanced T lymphocyte recruitment, oxidative stress tolerance, and iron accumulation. Under in vivo FTH-MRI guidance and monitoring, peritumoral transplantation of CXCL10-Nrf2-FTH-MSCs remarkably inhibited orthotopic GL261 and CT2A tumor growth in C57BL6 mice and prolonged animal survival. While ICB alone demonstrated no therapeutic impact, CXCL10-Nrf2-FTH-MSC transplantation combined with ICB demonstrated an enhanced anticancer effect for CT2A GBMs compared with transplanting it alone. Histology revealed that peritumorally injected CXCL10-Nrf2-FTH-MSCs survived longer in the TME, increased CXCL10 production, and ultimately remodeled the TME by increasing CD8+ T cells, interferon-γ+ cytotoxic T lymphocytes (CTLs), GzmB+ CTLs, and Th1 cells while reducing regulatory T cells (Tregs), exhausted CD8+ and exhausted CD4+ T cells.

CONCLUSIONS

MRI-guided peritumoral administration of CXCL10 and Nrf2-overexpressed MSCs can significantly limit GBM growth by revitalizing T lymphocytes within TME. The combination application of CXCL10-Nrf2-FTH-MSC transplantation and ICB therapy presents a potentially effective approach to treating GBM.

Peritumoral administration of IFNβ upregulated mesenchymal stem cells inhibits tumor growth in an orthotopic, immunocompetent rat glioma model

BACKGROUND

Immunotherapy with IFNβ is a promising strategy for treating malignant glioma. However, systemic administration of IFNβ is inadequate because of low intratumoral concentration and major adverse effects. This study aimed to determine whether mesenchymal stem cells (MSCs) can be used as cellular vehicles to locally deliver IFNβ for glioma therapy by using in vivo MRI tracking.

METHODS

A recombinant lentiviral vector encoding IFNβ and ferritin heavy chain (FTH) reporter genes was constructed to transduce MSCs. The effectiveness and safety of transduction were assessed. After the IFNβ and FTH overexpressed MSCs (IFNβ-FTH-MSCs) were transplanted into intracranial orthotopic rat F98 gliomas via peritumoral, intracerebral, intratumoral or intra-arterial injection, MRI was performed to track IFNβ-FTH-MSCs and to evaluate their therapeutic effect on glioma in vivo, as validated by histologic analysis, quantitative PCR and ELISA assays.

RESULTS

MSCs were efficiently and safely transduced to upregulate their IFNβ secretion and FTH expression by the constructed lentivirus. After peritumoral injection, IFNβ-FTH-MSCs appeared as hypointense signals on MRI, which gradually diminished but remained visible until 11 days. Compared with other administration routes, only peritumoral injection of IFNβ-FTH-MSCs showed a remarkable inhibition on the glioma growth. Nearly 30% of IFNβ-FTH-MSCs survived up to 11 days after peritumoral injection, while most of IFNβ-FTH-MSCs injected via other routes died within 11 days. IFNβ-FTH-MSCs grafted peritumorally secreted IFNβ persistently, leading to pronounced Batf3+ dendritic cells and CD8+ T lymphocyte infiltration within the glioma.

CONCLUSIONS

MSCs can be used as cellular vehicles of IFNβ to treat malignant glioma effectively via peritumoral injection.

Discriminative pattern of reduced cerebral blood flow in Parkinson's disease and Parkinsonism-Plus syndrome: an ASL-MRI study

BACKGROUND

Accurate identification of Parkinson's disease (PD) and Parkinsonism-Plus syndrome (PPS), especially in the early stage of the disease, is very important. The purpose of this study was to investigate the discriminative spatial pattern of cerebral blood flow (CBF) between patients with PD and PPS.

METHODS

Arterial spin labeling (ASL) perfusion-weighted imaging was performed in 20 patients with PD (mean age 56.35 ± 7.56 years), 16 patients with PPS (mean age 59.62 ± 6.89 years), and 17 healthy controls (HCs, mean age 54.17 ± 6.58 years). Voxel-wise comparison of the CBF was performed among PD, PPS, and HC groups. The receiver operating characteristic (ROC) curve was used to evaluate the performance of CBF in discriminating between PD and PPS. The relationship between CBF and non-motor neuropsychological scores was assessed by correlation analysis.

RESULTS

PD group showed a significantly decreased CBF in the right cerebelum_crus2, the left middle frontal gyrus (MFG), the triangle inferior frontal gyrus (IFG_Tri), the left frontal medial orbital gyrus (FG_Med_Orb) and the left caudate nucleus (CN) compared with the HC group (P < 0.05). Besides the above regions, the left supplementary motor area (SMA), the right thalamus had decreased CBF in the PPS group compared with the HC group (P < 0.05). PPS group had lower CBF value in the left MFG, the left IFG_Tri, the left CN, the left SMA, and the right thalamus compared with the PD group (P < 0.05). CBFs in left IFG_Tri, the left CN, the left SMA, and the right thalamus had moderate to high capacity in discriminating between PD and PPS patients (AUC 0.719-0.831). The CBF was positively correlated with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores in PD patients, while positively correlated with the MMSE, Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD) scores in PPS patients (P < 0.05).

CONCLUSION

PD and PPS patients have certain discriminative patterns of reduced CBFs, which can be used as a surrogate marker for differential diagnosis.

Quantitative Parameters of Diffusion Spectrum Imaging: HER2 Status Prediction in Patients With Breast Cancer

OBJECTIVE

To explore the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in preoperatively predicting human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer.

METHODS

In this prospective study, 114 and 56 female patients with invasive ductal carcinoma were consecutively included in a derivation cohort and an independent validation cohort, respectively. Each patient was categorized into HER2-positive or HER2-negative groups based on the pathologic result. All patients underwent DSI and conventional MRI including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). The tumor size, type of the time-signal intensity curve (TIC) from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, and quantitative parameters derived from DSI, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) of primary tumors, were measured and compared between the HER2-positive and HER2-negative groups in the derivation cohort. Univariable and multivariable logistic regression analyses were used to determine the potential independent predictors of HER2 status. The discriminative ability of quantitative parameters was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort.

RESULTS

In the derivation cohort, the tumor size, TIC type, and ADC values did not differ between the HER2-positive and HER2-negative groups (p = 0.126-0.961). DSI quantitative parameters including axial kurtosis of DKI (DKI_AK), non-Gaussianity (MAP_NG), axial non-Gaussianity (MAP_NGAx), radial non-Gaussianity (MAP_NGRad), return-to-origin probability (MAP_RTOP), return-to-axis probability of MAP (MAP_RTAP), and intracellular volume fraction of NODDI (NODDI_ICVF) were lower in the HER2-positive group than in the HER2-negative group (p ≤ 0.001-0.035). DSI quantitative parameters including radial diffusivity (DTI_RD), mean diffusivity of DTI (DTI_MD), mean squared diffusion (MAP_MSD), and q-space inverse variance of MAP (MAP_QIV) were higher in the HER2-positive group than in the HER2-negative group (p = 0.016-0.049). The ROC analysis showed that the area under the curve (AUC) of ADC was 0.632 and 0.568, respectively, in the derivation and validation cohorts. The AUC values of DSI quantitative parameters ranged from 0.628 to 0.700 and from 0.673 to 0.721, respectively, in the derivation and validation cohorts. Logistic regression analysis showed that only NODDI_ICVF was an independent predictor of HER2 status (p = 0.001), with an AUC of 0.700 and 0.721, respectively, in the derivation and validation cohorts.

CONCLUSIONS

DSI could be helpful for preoperative prediction of HER2, but DSI alone may not be sufficient in predicting HER2 status preoperatively in patients with breast cancer.