Radiotherapy-sensitized cancer immunotherapy via cGAS-STING immune pathway by activatable nanocascade reaction.

Radiotherapy-induced immune activation holds great promise for optimizing cancer treatment efficacy. Here, we describe a clinically used radiosensitizer hafnium oxide (HfO2) that was core coated with a MnO2 shell followed by a glucose oxidase (GOx) doping nanoplatform (HfO2@MnO2@GOx, HMG) to trigger ferroptosis adjuvant effects by glutathione depletion and reactive oxygen species production. This ferroptosis cascade potentiation further sensitized radiotherapy by enhancing DNA damage in 4T1 breast cancer tumor cells. The combination of HMG nanoparticles and radiotherapy effectively activated the damaged DNA and Mn2+-mediated cGAS-STING immune pathway in vitro and in vivo. This process had significant inhibitory effects on cancer progression and initiating an anticancer systemic immune response to prevent distant tumor recurrence and achieve long-lasting tumor suppression of both primary and distant tumors. Furthermore, the as-prepared HMG nanoparticles "turned on" spectral computed tomography (CT)/magnetic resonance dual-modality imaging signals, and demonstrated favorable contrast enhancement capabilities activated by under the GSH tumor microenvironment. This result highlighted the potential of nanoparticles as a theranostic nanoplatform for achieving molecular imaging guided tumor radiotherapy sensitization induced by synergistic immunotherapy.

Double-Layered Hollow Mesoporous Cuprous Oxide Nanoparticles for Double Drug Sequential Therapy of Tumors.

Cancer stem cells (CSCs) are one of the determinants of tumor heterogeneity and are characterized by self-renewal, high tumorigenicity, invasiveness, and resistance to various therapies. To overcome the resistance of traditional tumor therapies resulting from CSCs, a strategy of double drug sequential therapy (DDST) for CSC-enriched tumors is proposed in this study and is realized utilizing the developed double-layered hollow mesoporous cuprous oxide nanoparticles (DL-HMCONs). The high drug-loading contents of camptothecin (CPT) and all-trans retinoic acid (ATRA) demonstrate that the DL-HMCON can be used as a generic drug delivery system. ATRA and CPT can be sequentially loaded in and released from CPT3@ATRA3@DL-HMCON@HA. The DDST mechanisms of CPT3@ATRA3@DL-HMCON@HA for CSC-containing tumors are demonstrated as follows: 1) the first release of ATRA from the outer layer induces differentiation from CSCs with high drug resistance to non-CSCs with low drug resistance; 2) the second release of CPT from the inner layer causes apoptosis of non-CSCs; and 3) the third release of Cu+ from DL-HMCON itself triggers the Fenton-like reaction and glutathione depletion, resulting in ferroptosis of non-CSCs. This CPT3@ATRA3@DL-HMCON@HA is verified to possess high DDST efficacy for CSC-enriched tumors with high biosafety.

Kilogram scale facile synthesis and systematic characterization of a Gd-macrochelate as T1-weighted magnetic resonance imaging contrast agent.

To overcome the problems of commercial magnetic resonance imaging (MRI) contrast agents (CAs) (i.e., small molecule Gd chelates), we have proposed a new concept of Gd macrochelates based on the coordination of Gd3+ and macromolecules, e.g., poly(acrylic acid) (PAA). To further decrease the r2/r1 ratio of the reported Gd macrochelates that is an important factor for T1 imaging, in this study, a superior macromolecule hydrolyzed polymaleic anhydride (HPMA) was found to coordinate Gd3+. The synthesis conditions were optimized and the generated Gd-HPMA macrochelate was systematically characterized. The obtained Gd-HPMA29 synthesized in a 100 L of reactor has a r1 value of 16.35 mM-1 s-1 and r2/r1 ratio of 2.05 at 7.0 T, a high Gd yield of 92.7% and a high product weight (1074 g), which demonstrates the feasibility of kilogram scale facile synthesis. After optimization of excipients and sterilization at a high temperature, the obtained Gd-HPMA30 formulation has a pH value of 7.97, osmolality of 691 mOsmol/kg water, density of 1.145 g/mL, and viscosity of 2.2 cP at 20 â„ƒ or 1.8 cP at 37 â„ƒ, which meet all specifications and physicochemical criteria for clinical injections indicating the immense potential for clinical applications.

Differentiating the Invasiveness of Lung Adenocarcinoma Manifesting as Ground Glass Nodules: Combination of Dual-energy CT Parameters and Quantitative-semantic Features.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of dual-energy CT (DECT) parameters and quantitative-semantic features for differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules (GGNs). MATERIALS AND METHODS: Between June 2022 and September 2023, 69 patients with 74 surgically resected GGNs who underwent DECT examinations were included. CT numbers on virtual monochromatic images were calculated at 40-130 keV generated from DECT. Quantitative morphological measurements and semantic features were evaluated on unenhanced CT images and compared between pathologically confirmed adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive lung adenocarcinoma (IAC). Multivariable logistic regression analysis was used to identify independent predictors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test. RESULTS: Monochromatic CT numbers at 40-130 keV were significantly higher in IAC than in AIS-MIA (all P < 0.05). Multivariate logistic analysis revealed that CT number of 130 keV (odds ratio [OR] = 1.02, P = 0.013), maximum cross-sectional long diameter (OR =1.40, P = 0.014), deep or moderate lobulation sign (OR =19.88, P = 0.005), and abnormal intranodular vessel morphology (OR = 25.57, P = 0.017) were independent predictors of IAC. The combined prediction model showed a favorable differentiation performance with an AUC of 0.966 (95.2% sensitivity, 94.3% specificity, 94.8% accuracy), which was significantly higher than that for each risk factor (AUC = 0.791-0.822, all P < 0.05). CONCLUSION: A multi-parameter combined prediction model integrating monochromatic CT numbers from DECT and quantitative-semantic features is promising for the preoperative discrimination of IAC and AIS-MIA in GGN-predominant lung adenocarcinoma.

MRI-Guided Tumor Therapy Based on Synergy of Ferroptosis, Immunosuppression Reversal and Disulfidptosis.

Triple negative breast cancer (TNBC) cells have a high demand for oxygen and glucose to fuel their growth and spread, shaping the tumor microenvironment (TME) that can lead to a weakened immune system by hypoxia and increased risk of metastasis. To disrupt this vicious circle and improve cancer therapeutic efficacy, a strategy is proposed with the synergy of ferroptosis, immunosuppression reversal and disulfidptosis. An intelligent nanomedicine GOx-IA@HMON@IO is successfully developed to realize this strategy. The Fe release behaviors indicate the glutathione (GSH)-responsive degradation of HMON. The results of titanium sulfate assay, electron spin resonance (ESR) spectra, 5,5'-Dithiobis-(2-nitrobenzoic acid (DTNB) assay and T1 -weighted magnetic resonance imaging (MRI) demonstrate the mechanism of the intelligent iron atom (IA)-based cascade reactions for GOx-IA@HMON@IO, generating robust reactive oxygen species (ROS). The results on cells and mice reinforce the synergistic mechanisms of ferroptosis, immunosuppression reversal and disulfidptosis triggered by the GOx-IA@HMON@IO with the following steps: 1) GSH peroxidase 4 (GPX4) depletion by disulfidptosis; 2) IA-based cascade reactions; 3) tumor hypoxia reversal; 4) immunosuppression reversal; 5) GPX4 depletion by immunotherapy. Based on the synergistic mechanisms of ferroptosis, immunosuppression reversal and disulfidptosis, the intelligent nanomedicine GOx-IA@HMON@IO can be used for MRI-guided tumor therapy with excellent biocompatibility and safety.

Cancer Radiosensitization Nanoagent to Activate cGAS-STING Pathway for Molecular Imaging Guided Synergistic Radio/Chemo/Immunotherapy.

Immunotherapy has emerged as an innovative strategy with the potential to improve outcomes in cancer patients. Recent evidence indicates that radiation-induced DNA damage can activate the cyclic-GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway to enhance the antitumor immune response. Even so, only a small fraction of patients currently benefits from radioimmunotherapy due to the radioresistance and the inadequate activation of the cGAS-STING pathway. Herein, this work integrates hafnium oxide (HfO2 ) nanoparticles (radiosensitizer) and 7-Ethyl-10-hydroxycamptothecin (SN38, chemotherapy drug, STING agonist) into a polydopamine (PDA)-coated core-shell nanoplatform (HfO2 @PDA/Fe/SN38) to achieve synergistic chemoradiotherapy and immunotherapy. The co-delivery of HfO2 /SN38 greatly enhances radiotherapy efficacy by effectively activating the cGAS-STING pathway, which then triggers dendritic cells maturation and CD8+ T cells recruitment. Consequently, the growth of both primary and abscopal tumors in tumor-bearing mice is efficiently inhibited. Moreover, the HfO2 @PDA/Fe/SN38 complexes exhibit favorable magnetic resonance imaging (MRI)/photoacoustic (PA) bimodal molecular imaging properties. In summary, these developed multifunctional complexes have the potential to intensify immune activation to realize simultaneous cancer Radio/Chemo/Immunotherapy for clinical translation.

Kilogram-Scale Synthesis of Extremely Small Gadolinium Oxide Nanoparticles as a T1-Weighted Contrast Agent for Magnetic Resonance Imaging.

Magnetic resonance imaging contrast agents are frequently used in clinics to enhance the contrast between diseased and normal tissues. The previously reported poly(acrylic acid) stabilized exceedingly small gadolinium oxide nanoparticles (ES-GdON-PAA) overcame the problems of commercial Gd chelates, but limitations still exist, i.e., high r2/r1 ratio, long blood circulation half-life, and no data for large scale synthesis and formulation optimization. In this study, polymaleic acid (PMA) is found to be an ideal stabilizer to synthesize ES-GdONs. Compared with ES-GdON-PAA, the PMA-stabilized ES-GdON (ES-GdON-PMA) has a lower r2/r1 ratio (2.05, 7.0 T) and a lower blood circulation half-life (37.51 min). The optimized ES-GdON-PMA-9 has an exceedingly small particle size (2.1 nm), excellent water dispersibility, and stability. A facile, efficient, and environmental friendly synthetic method is developed for large-scale synthesis of the ES-GdONs-PMA. The weight of the optimized freeze-dried ES-GdON-PMA-26 synthesized in a 20 L of reactor reaches the kilogram level. The formulation optimization is also finished, and the concentrated ES-GdON-PMA-26 formulation (CGd = 100 mm) after high-pressure steam sterilization possesses eligible physicochemical properties (i.e., pH value, osmolality, viscosity, and density) for investigational new drug application.

Combining ADC values in DWI with rCBF values in arterial spin labeling (ASL) for the diagnosis of mild cognitive impairment (MCI).

We aimed to investigate the role of combined apparent diffusion coefficient (ADC) values and relative cerebral blood flow (rCBF) values in the diagnosis of mild cognitive impairment (MCI) patients. The present prospective research enrolled 156 MCI patients and 58 healthy elderly people who came to our hospital from January 2021 to February 2023. T1W, T2W, diffusion-weighted imaging, and arterial spin labeling sequences were performed on all subjects, and ADC values and rCBF values were measured at the workstation. Clinical and demographic data of all patients were collected while mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scores were used to assess patients' cognitive abilities. The MCI group had significantly lower rCBF values in the left frontal lobe, left occipital lobe, right frontal lobe, and right occipital lobe than the HC group. The ADC values in the left frontal lobe as well as the right frontal lobe were remarkably elevated in the MCI group than in the HC group. MoCA and MMSE scores were positively correlated with rCBF values in the left frontal, right frontal, left occipital, and right occipital lobes and negatively correlated with ADC values in the left and right frontal lobes. Combined ADC values and rCBF values from the left frontal lobe for the diagnosis of MCI had a higher sensitivity and specificity with the AUC was 0.877, sensitivity 81.0%, specificity 82.7%. Additionally, pressure fasting plasma glucose, ADC of the left frontal lobe, right frontal lobe, rCBF of left frontal lobe and rCBF of left frontal lobe were the risk factors of patients with MCI. In summary, our results indicated that the ADC values and rCBF values were changed in MCI group compared to HC group and correlated with MMSE and MoCA scores.

Proton pump inhibitor-enhanced nanocatalytic ferroptosis induction for stimuli-responsive dual-modal molecular imaging guided cancer radiosensitization.

Although radiotherapeutic efficiency has been revealed to be positively correlated with ferroptosis, the neutral/alkaline cytoplasm pH value of tumor cells remains an intrinsic challenge for efficient Fenton/Fenton-like reaction-based ferroptosis induction. Herein, PEGylated hollow mesoporous organosilica nanotheranostics (HMON)-GOx@MnO2 nanoparticles (HGMP NPs) were designed as a ferroptosis inducer, which could specifically release Mn2+ in tumor cells to activate the Fenton-like reaction for ferroptosis induction. Proton pump inhibitors (PPIs) were synchronously administered for cytoplasm pH level regulation by inhibiting V-H+-ATPases activity, enhancing Fenton-like reaction-based ferroptosis induction. Moreover, reactive oxygen species production was facilitated via the glucose oxidase triggered cascade catalytic reaction by utilizing intracellular ß-D-glucose for H2O2 self-supply and generation of additional cytoplasm H+. The PPI enhanced ferroptosis inducing nanosystem effectively inhibited tumor growth both in vitro and in vivo for tumor-specific ferroptosis induction and radiotherapy sensitization, suggesting that PPI administration could be an efficient adjuvant to reinforce Fenton/Fenton-like reaction-based ferroptosis induction for radiosensitization. STATEMENT OF SIGNIFICANCE: The cytoplasm pH value of tumor cells is typically neutral to alkaline, which is higher than that of the Fenton/Fenton-like reaction desired acidic environments, hindering its efficiency. In this study, PEGylated hollow mesoporous organosilica nanotheranostics (HMON)-GOx@MnO2 nanoparticles were synthesized as a ferroptosis inducer, which could specifically release Mn2+ via depleting glutathione and then activate the Fenton-like reaction in the tumor microenvironment. The glucose oxidase was applied for H2O2 self-supply and addition of cytoplasm H+ to further boost the Fenton-like reaction. We found that proton pump inhibitors (PPIs) increased intracellular acidification by inhibiting the activity of V-H+-ATPases to enhance the Fenton reaction-based ferroptosis induction, suggesting PPIs administration could be a feasible strategy to reinforce ferroptosis induction for radiosensitization.

Kartogenin (KGN)/synthetic melanin nanoparticles (SMNP) loaded theranostic hydrogel scaffold system for multiparametric magnetic resonance imaging guided cartilage regeneration.

Cartilage regeneration after injury is still a great challenge in clinics, which suffers from its avascularity and poor proliferative ability. Herein we designed a novel biocompatible cellulose nanocrystal/GelMA (gelatin-methacrylate anhydride)/HAMA (hyaluronic acid-methacrylate anhydride)-blended hydrogel scaffold system, loaded with synthetic melanin nanoparticles (SMNP) and a bioactive drug kartogenin (KGN) for theranostic purpose. We found that the SMNP-KGN/Gel showed favorable mechanical property, thermal stability, and distinct magnetic resonance imaging (MRI) contrast enhancement. Meanwhile, the sustained release of KGN could recruit bone-derived mesenchymal stem cells to proliferate and differentiate into chondrocytes, which promoted cartilage regeneration in vitro and in vivo. The hydrogel degradation and cartilage restoration were simultaneously monitored by multiparametric MRI for 12 weeks, and further confirmed by histological analysis. Together, these results validated the multifunctional hydrogel as a promising tissue engineering platform for noninvasive imaging-guided precision therapy in cartilage regenerative medicine.

Clinical prediction of magnetic resonance image compilation in patients with mild cognitive impairment.

This study aims to investigate the clinical prediction of magnetic resonance image compilation (MAGiC) and magnetic resonance image (MRI) in early diagnosis of the patients with mild cognitive impairment. This study is a retrospective randomized controlled clinical trial, and all patients are divided into following two groups: experiment group and control group. Patients in the experiment group are detected by MAGiC, and patients in the control group are detected by MRI; the clinical material from the two groups of patients with MCI are collected, and then Wechsler Memory Scale-Logical Memory (WMS-LM) and Mini-Mental State Examination (MMSE) are recorded by follow-up. Images by MAGiC have higher accuracy and definition compared with those by MRI. WMS-LM score and MMSE score in the experiment group are significantly better than those in the control group. We can conclude that MAGiC is a promising way to evaluate the clinical prediction in patients with MCI.

Parametric MRI Detects Aristolochic Acid Induced Acute Kidney Injury.

Exposure to aristolochic acid (AA) is of increased concern due to carcinogenic and nephrotoxic effects, and incidence of aristolochic acid nephropathy (AAN) is increasing. This study characterizes renal alterations during the acute phase of AAN using parametric magnetic resonance imaging (MRI). An AAN and a control group of male Wistar rats received administration of aristolochic acid I (AAI) and polyethylene glycol (PEG), respectively, for six days. Both groups underwent MRI before and 2, 4 and 6 days after AAI or PEG administration. T2 relaxation times and apparent diffusion coefficients (ADCs) were determined for four renal layers. Serum creatinine levels (sCr) and blood urea nitrogen (BUN) were measured. Tubular injury scores (TIS) were evaluated based on histologic findings. Increased T2 values were detected since day 2 in the AAN group, but decreased ADCs and increased sCr levels and BUN were not detected until day 4. Significant linear correlations were observed between T2 of the cortex and the outer stripe of outer medulla and TIS. Our results demonstrate that parametric MRI facilitates early detection of renal injury induced by AAI in a rat model. T2 mapping may be a valuable tool for assessing kidney injury during the acute phase of AAN.

Machine learning-based combined nomogram for predicting the risk of pulmonary invasive fungal infection in severely immunocompromised patients.

Background: Early and accurate diagnosis of invasive fungal infection (IFI) is pivotal for the initiation of effective antifungal therapy for patients with hematologic malignancies. Methods: This retrospective study involved 235 patients with hematologic malignancies and pulmonary infections diagnosed as IFIs (n=118) or bacterial pneumonia (n=117). Patients were randomly divided into training (n=188) and validation (n=47) datasets. Four feature selection methods with nine classifiers were implemented to select the optimal machine learning (ML) model using five-fold cross-validation. A radiomic signature was constructed using a linear ML algorithm, and a radiomic score (Radscore) was calculated. The combined model was developed with the Radscore, the significant clinical and radiologic factors were selected using multivariable logistic regression, and the results were presented as a clinical radiomic nomogram. A prospective pilot study was also conducted to compare the classification performance of the combined nomogram with practicing radiologists. Results: Significant differences were found in the Radscore between IFI and bacterial pneumonia patients in the training (0.683 vs. -0.724, P<0.001) and validation set (0.353 vs. -0.717, P=0.002). The combined model showed good discrimination performance in the validation cohort [area under the curve (AUC) =0.844] and outperformed the clinical (AUC =0.696) and radiomics (AUC =0.767) model alone (both P<0.05). Conclusions: The clinical radiomic nomogram can serve as a promising predictive tool for IFI in patients with hematologic malignancies.

Diagnosis of Idiopathic Pulmonary Fibrosis in High-Resolution Computed Tomography Scans Using a Combination of Handcrafted Radiomics and Deep Learning.

Purpose: To develop handcrafted radiomics (HCR) and deep learning (DL) based automated diagnostic tools that can differentiate between idiopathic pulmonary fibrosis (IPF) and non-IPF interstitial lung diseases (ILDs) in patients using high-resolution computed tomography (HRCT) scans. Material and Methods: In this retrospective study, 474 HRCT scans were included (mean age, 64.10 years ± 9.57 [SD]). Five-fold cross-validation was performed on 365 HRCT scans. Furthermore, an external dataset comprising 109 patients was used as a test set. An HCR model, a DL model, and an ensemble of HCR and DL model were developed. A virtual in-silico trial was conducted with two radiologists and one pulmonologist on the same external test set for performance comparison. The performance was compared using DeLong method and McNemar test. Shapley Additive exPlanations (SHAP) plots and Grad-CAM heatmaps were used for the post-hoc interpretability of HCR and DL models, respectively. Results: In five-fold cross-validation, the HCR model, DL model, and the ensemble of HCR and DL models achieved accuracies of 76.2 ± 6.8, 77.9 ± 4.6, and 85.2 ± 2.7%, respectively. For the diagnosis of IPF and non-IPF ILDs on the external test set, the HCR, DL, and the ensemble of HCR and DL models achieved accuracies of 76.1, 77.9, and 85.3%, respectively. The ensemble model outperformed the diagnostic performance of clinicians who achieved a mean accuracy of 66.3 ± 6.7% (p < 0.05) during the in-silico trial. The area under the receiver operating characteristic curve (AUC) for the ensemble model on the test set was 0.917 which was significantly higher than the HCR model (0.817, p = 0.02) and the DL model (0.823, p = 0.005). The agreement between HCR and DL models was 61.4%, and the accuracy and specificity for the predictions when both the models agree were 93 and 97%, respectively. SHAP analysis showed the texture features as the most important features for IPF diagnosis and Grad-CAM showed that the model focused on the clinically relevant part of the image. Conclusion: Deep learning and HCR models can complement each other and serve as useful clinical aids for the diagnosis of IPF and non-IPF ILDs.

Rapid synthesis of 'yolk-shell'-like nanosystem for MR molecular and chemo-radio sensitization.

Though amounts of attempts about nanomedicine for chemo-radiotherapy have been made, more efficient strategies for chemo-radio therapy enhancement still need to be studied and perfected. Herein, a 'yolk-shell'-like nanostructure (Bi2S3@mBixMnyOz nanosystem) was facilely constructed by directly using radiosensitizer Bi2S3 nanorods (NRs) as a partial sacrificial template. Then, the chemotherapeutic drug doxorubicin (DOX) loaded PEGylated Bi2S3@mBixMnyOz nanosystem (PBmB-DOX) was constructed, which could realize tumor microenvironment (TME)-responsive drug release for chemotherapy sensitivity enhancement. And the Bi2S3 NRs core could deposit more radiant energy to improve the radiotherapy sensitivity. Meanwhile, the compounds shell could catalyze H2O2 to generate O2, so as to alleviate tumor hypoxia for further chemo-radio therapy sensitization enhancement. More importantly, ferroptosis was participated in the process of PBmB-induced therapy via glutathione (GSH)-depletion mediated GPX4 inactivation, together with Mn ions induced chemodynamic therapy (Fenton-like reaction), which made additional contributions to increase the therapeutic efficacy. Last but not least, the GSH-stimulated degradation of compounds shell could contribute to self-enhanced T1-MR imaging activation, which allowed on-demand tumor diagnosis. In this work, the synthetic strategy that directly using Bi2S3 NRs as a partial sacrificial template to rapidly synthesize the 'yolk-shell'-like nanostructure for nanomedical application has rarely been reported before. And the in vitro and in vivo results suggest that our 'yolk-shell'-like PBmB-DOX nanosystem holds great promise to regulate TME for tumor-specific diagnosis and synergistic therapy.

A Handcrafted Radiomics-Based Model for the Diagnosis of Usual Interstitial Pneumonia in Patients with Idiopathic Pulmonary Fibrosis.

The most common idiopathic interstitial lung disease (ILD) is idiopathic pulmonary fibrosis (IPF). It can be identified by the presence of usual interstitial pneumonia (UIP) via high-resolution computed tomography (HRCT) or with the use of a lung biopsy. We hypothesized that a CT-based approach using handcrafted radiomics might be able to identify IPF patients with a radiological or histological UIP pattern from those with an ILD or normal lungs. A total of 328 patients from one center and two databases participated in this study. Each participant had their lungs automatically contoured and sectorized. The best radiomic features were selected for the random forest classifier and performance was assessed using the area under the receiver operator characteristics curve (AUC). A significant difference in the volume of the trachea was seen between a normal state, IPF, and non-IPF ILD. Between normal and fibrotic lungs, the AUC of the classification model was 1.0 in validation. When classifying between IPF with a typical HRCT UIP pattern and non-IPF ILD the AUC was 0.96 in validation. When classifying between IPF with UIP (radiological or biopsy-proved) and non-IPF ILD, an AUC of 0.66 was achieved in the testing dataset. Classification between normal, IPF/UIP, and other ILDs using radiomics could help discriminate between different types of ILDs via HRCT, which are hardly recognizable with visual assessments. Radiomic features could become a valuable tool for computer-aided decision-making in imaging, and reduce the need for unnecessary biopsies.

Functionalized Au@Cu-Sb-S Nanoparticles for Spectral CT/Photoacoustic Imaging-Guided Synergetic Photo-Radiotherapy in Breast Cancer.

BACKGROUND: Radiotherapy (RT) is clinically well-established cancer treatment. However, radioresistance remains a significant issue associated with failure of RT. Phototherapy-induced radiosensitization has recently attracted attention in translational cancer research. METHODS: Cu-Sb-S nanoparticles (NPs) coated with ultra-small Au nanocrystals (Au@Cu-Sb-S) were synthesized and characterized. The biosafety profiles, absorption of near-infrared (NIR) laser and radiation-enhancing effect of the NPs were evaluated. In vitro and in vivo spectral computed tomography (CT) imaging and photoacoustic (PA) imaging were performed in 4T1 breast cancer-bearing mice. The synergetic radio-phototherapy was assessed by in vivo tumor inhibition studies. RESULTS: Au@Cu-Sb-S NPs were prepared by in situ growth of Au NCs on the surface of Cu-Sb-S NPs. The cell viability experiments showed that the combination of Au@Cu-Sb-S+NIR+RT was significantly more cytotoxic to tumor cells than the other treatments at concentrations above 25 ppm Sb. In vitro and in vivo spectral CT imaging demonstrated that the X-ray attenuation ability of Au@Cu-Sb-S NPs was superior to that of the clinically used Iodine, particularly at lower KeV levels. Au@Cu-Sb-S NPs showed a concentration-dependent and remarkable PA signal brightening effect. In vivo tumor inhibition studies showed that the prepared Au@Cu-Sb-S NPs significantly suppressed tumor growth in 4T1 breast cancer-bearing mice treated with NIR laser irradiation and an intermediate X-ray dose (4 Gy). CONCLUSION: These results indicate that Au@Cu-Sb-S integrated with spectral CT, PA imaging, and phototherapy-enhanced radiosensitization is a promising multifunctional theranostic nanoplatform for clinical applications.

A fully automatic artificial intelligence-based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis.

OBJECTIVES: An accurate and rapid diagnosis is crucial for the appropriate treatment of pulmonary tuberculosis (TB). This study aims to develop an artificial intelligence (AI)-based fully automated CT image analysis system for detection, diagnosis, and burden quantification of pulmonary TB. METHODS: From December 2007 to September 2020, 892 chest CT scans from pathogen-confirmed TB patients were retrospectively included. A deep learning-based cascading framework was connected to create a processing pipeline. For training and validation of the model, 1921 lesions were manually labeled, classified according to six categories of critical imaging features, and visually scored regarding lesion involvement as the ground truth. A "TB score" was calculated based on a network-activation map to quantitively assess the disease burden. Independent testing datasets from two additional hospitals (dataset 2, n = 99; dataset 3, n = 86) and the NIH TB Portals (n = 171) were used to externally validate the performance of the AI model. RESULTS: CT scans of 526 participants (mean age, 48.5 ± 16.5 years; 206 women) were analyzed. The lung lesion detection subsystem yielded a mean average precision of the validation cohort of 0.68. The overall classification accuracy of six pulmonary critical imaging findings indicative of TB of the independent datasets was 81.08-91.05%. A moderate to strong correlation was demonstrated between the AI model-quantified TB score and the radiologist-estimated CT score. CONCLUSIONS: The proposed end-to-end AI system based on chest CT can achieve human-level diagnostic performance for early detection and optimal clinical management of patients with pulmonary TB. KEY POINTS: • Deep learning allows automatic detection, diagnosis, and evaluation of pulmonary tuberculosis. • Artificial intelligence helps clinicians to assess patients with tuberculosis. • Pulmonary tuberculosis disease activity and treatment management can be improved.