CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.

BACKGROUND: Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients. METHODS: This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group. The radiomic features of the whole lung volume were extracted. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection and radiomic signature construction. A radiomic nomogram was established by combining the radiomic score and clinical factors. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive performance of the radiomic nomogram in the training, internal validation, and independent external validation cohorts. RESULTS: Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model. The area under the curve (AUC) of the radiomic model in the training, internal, and independent external validation cohorts were 0.888 [95% confidence interval (CI) 0.869-0.906], 0.874 (95%CI 0.844-0.904) and 0.846 (95%CI 0.822-0.870), respectively. All were higher than the clinical model (AUC were 0.732, 0.714, and 0.777, respectively, P < 0.001). DCA demonstrated that the nomogram constructed by combining radiomic score, age, sex, height, and smoking status was superior to the clinical factor model. CONCLUSIONS: The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

CT-based whole lung radiomics nomogram: a tool for identifying the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease.

OBJECTIVES: To evaluate the value of CT-based whole lung radiomics nomogram for identifying the risk of cardiovascular disease (CVD) in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: A total of 974 patients with COPD were divided into a training cohort (n = 402), an internal validation cohort (n = 172), and an external validation cohort (n = 400) from three hospitals. Clinical data and CT findings were analyzed. Radiomics features of whole lung were extracted from the non-contrast chest CT images. A radiomics signature was constructed with algorithms. Combined with the radiomics score and independent clinical factors, multivariate logistic regression analysis was used to establish a radiomics nomogram. ROC curve was used to analyze the prediction performance of the model. RESULTS: Age, weight, and GOLD were the independent clinical factors. A total of 1218 features were extracted and reduced to 15 features to build the radiomics signature. In the training cohort, the combined model (area under the curve [AUC], 0.731) showed better discrimination capability (p < 0.001) than the clinical factors model (AUC, 0.605). In the internal validation cohort, the combined model (AUC, 0.727) performed better (p = 0.032) than the clinical factors model (AUC, 0.629). In the external validation cohort, the combined model (AUC, 0.725) performed better (p < 0.001) than the clinical factors model (AUC, 0.690). Decision curve analysis demonstrated the radiomics nomogram outperformed the clinical factors model. CONCLUSION: The CT-based whole lung radiomics nomogram has the potential to identify the risk of CVD in patients with COPD. CLINICAL RELEVANCE STATEMENT: This study helps to identify cardiovascular disease risk in patients with chronic obstructive pulmonary disease on chest CT scans. KEY POINTS: • To investigate the value of CT-based whole lung radiomics features in identifying the risk of cardiovascular disease in chronic obstructive pulmonary disease patients. • The radiomics nomogram showed better performance than the clinical factors model to identify the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. • The radiomics nomogram demonstrated excellent performance in the training, internal validation, and external validation cohort (AUC, 0.731; AUC, 0.727; AUC, 0.725).

An Adaptable Nanoprobe Integrated with Quantitative T1 -Mapping MRI for Accurate Differential Diagnosis of Multidrug-Resistant Lung Cancer.

Multidrug resistance (MDR) is one of the major factors causing failure of non-small-cell lung cancer (NSCLC) chemotherapy. Real-time and accurate differentiation between drug-resistant and sensitive NSCLC is of primary importance for guiding the subsequent treatments and improving the therapeutic outcome. However, there is no effective method to provide such an accurate differentiation. This study creates an innovative strategy of integrating H2 O2 -responsive nanoprobes with the quantitative T1 -mapping magnetic resonance imaging (MRI) technique to achieve an accurate differential diagnosis between drug-resistant and sensitive NSCLC in light of differences in H2 O2 content in the tumor microenvironment (TME). The result demonstrates that the synthesized MIL-53(Fe)@MnO2 nanocomposites possess an excellent capability of shortening the cancer longitudinal relaxation time (T1 ) when meeting H2 O2 in TME. T1 -mapping MRI could sensitively detect this T1 variation (about 2.6-fold that of T1-weighted imaging (T1 WI)) to accurately differentiate the H2 O2 content between drug-resistant and sensitive NSCLC. In addition, the quantitative data provided by the T1 -mapping MRI dedicates correct comparison across imaging tests and is more reliable than T1 WI, thus giving it a chance for precise assessment of the anti-cancer effect. This innovative strategy of merging TME adaptable nanoprobes with the quantitative MRI technique provides a new approach for the precise diagnosis of multidrug-resistant NSCLC.

Diagnostic Ability of Perivascular Fat Attenuation Index in Predicting Atherosclerotic Plaque Formation Proximal to Myocardial Bridging of the Left Anterior Descending Artery within 3 Years.

RATIONALE AND OBJECTIVES: This study was designed to investigate the association between the perivascular fat attenuation index (FAI) and atherosclerotic plaque formation proximal to myocardial bridging (MB) of the left anterior descending artery (LAD) within 3 years. MATERIALS AND METHODS: LAD-MB patients who underwent coronary computed tomography angiography at least twice between January 2016 and December 2022 were retrospectively included in this study. In total, 99 LAD-MB patients were included in the study. Based on the formation of atherosclerotic plaques proximal to LAD-MB during follow-up, the patients were classified into two groups: LAD-MB with plaque formation and LAD-MB without plaque formation within 3 years. The anatomical features, clinical factors, and proximal perivascular FAI of LAD-MB were measured and recorded. The association of the previously mentioned factors with the presence of atherosclerotic plaque proximal to LAD-MB was determined. RESULTS: The results showed that MB length, MB stenosis, and the perivascular FAI were significant predictors of the formation of atherosclerotic plaques proximal to LAD-MB. The area under the curve of the combined predictive model incorporating MB length, MB stenosis, and the perivascular FAI was 0.901(95% confidence interval: 0.824-0.952), with higher diagnostic performance than any other single parameter (all P < 0.05). Moreover, dynamic changes in the perivascular FAI of the vascular segments proximal to LAD-MB were higher in high-risk plaques than in non-high-risk plaques (P = 0.003). CONCLUSION: The combined use of the perivascular FAI, MB length, and MB stenosis may enable prediction of the probability of atherosclerotic plaque formation proximal to LAD-MB within 3 years. Dynamic changes in perivascular FAI were associated with the vulnerability of plaques proximal to LAD-MB.

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction.

Purpose: Accurate prediction of the progression to severe stroke in initially diagnosed nonsevere patients with acute-subacute anterior circulation nonlacuna ischemic infarction (ASACNLII) is important in making clinical decision. This study aimed to apply a machine learning method to predict if the initially diagnosed nonsevere patients with ASACNLII would progress to severe stroke by using diffusion-weighted images and clinical information on admission. Methods: This retrospective study enrolled 344 patients with ASACNLII from June 2017 to August 2020 on admission, and 108 cases progressed to severe stroke during hospitalization within 3-21 days. The entire data were randomized into a training set (n = 271) and an independent test set (n = 73). A U-Net neural network was employed for automatic segmentation and volume measurement of the ischemic lesions. Predictive models were developed and used for evaluating the progression to severe stroke using different feature sets (the volume data, the clinical data, and the combination) and machine learning methods (random forest, support vector machine, and logistic regression). Results: The U-Net showed high correlation with manual segmentation in terms of Dice coefficient of 0.806 and R 2 value of the volume measurements of 0.960 in the test set. The random forest classifier of the volume + clinical combination achieved the best area under the receiver operating characteristic curve of 0.8358 (95% CI 0.7321-0.9269), and the accuracy, sensitivity, and specificity were 0.7780 (0.7397-0.7945), 0.7695 (0.6102-0.9074), and 0.8686 (0.6923-1.0), respectively. The Shapley additive explanation diagram showed the volume variable as the most important predictor. Conclusion: The U-Net was fully automatic and showed a high correlation with manual segmentation. An integrated approach combining clinical variables and stroke lesion volumes that were derived from the advanced machine learning algorithms had high accuracy in predicting the progression to severe stroke in ASACNLII patients.

Luminal diameter ratio of Vieussens' arterial ring is valuable in determining appropriate clinical management for patients with pathologic Vieussens' arterial ring.

BACKGROUND: Although the adverse events of pathologic Vieussens' arterial ring (VAR) have been reported, it is difficult to determine optimal clinical management. Thus, we hypothesized that the luminal diameter ratio of VAR obtained from coronary computed tomography angiography (CCTA) could be used as a clinical tool to inform appropriate patient management. METHOD: A total of 29 patients with pathologic VAR were retrospectively recruited for this study. The VAR luminal diameter ratio was defined as a quotient of VAR fistula divided by the orifice of RCA or LAD, based on which, patients were divided into small fistula group and large fistula group. The AUC, sensitivity, specificity, positive and negative predictive values were obtained from ROC curve. The cutoff value of the VAR luminal diameter ratio was calculated and assessed during the follow-up. RESULTS: The VAR luminal diameter ratio of fistula/RCA orifice was 0.505 ± 0.098 in small fistula group and 1.020 ± 0.150 in large fistula group. The VAR luminal diameter ratio of fistula/LAD orifice was 0.507 ± 0.123 in small fistula group and 1.039 ± 0.151 in large group. The value was correlated with the choice of the treatment (r = 0.643 p < 0.01, r = 0.627 p < 0.01). The AUC, sensitivity, specificity, positive and negative predictive values were 0.803, 54.5%, 100%, 100% and 78.3% of the fistula/RCA orifice ratio and 0.833, 63.64%, 94.44%, 87.5% and 81.0% of the fistula/LAD orifice ratio, respectively. The cutoff values of both fistula/RCA orifice and fistula/LAD orifice ratios were 0.676. CONCLUSIONS: The VAR luminal diameter ratio may be a valuable index to determine appropriate treatment for patients with pathologic VAR.

Actively Targeted Magnetothermally Responsive Nanocarriers/Doxorubicin for Thermochemotherapy of Hepatoma.

Nanodrug-delivery systems modified with targeting molecules allow antitumor drugs to localize to tumor sites efficiently. CD147 protein is expressed highly on hepatoma cells. Firstly, we synthesized magnetothermally responsive nanocarriers/doxorubicin (MTRN/DOX) which was composed of manganese zinc (Mn-Zn) ferrite magnetic nanoparticles, amphiphilic and thermosensitivity copolymer drug carriers together with DOX. Then CD147-MTRN/DOX was formed with MTRN/DOX and monoclonal antibody that specifically binds to CD147 protein. It could target hepatoma cells actively and improve the DOX concentration in the tumor sites. Subsequently, an external alternating magnetic field elevated the temperature of the thermomagnetic particles, resulting in structural changes in the thermosensitive copolymer drug carriers, thereby releasing DOX. Hence, CD147-MTRN/DOX could enhance the responsiveness of hepatoma cells to the pre-existing chemotherapy drugs owing to active targeting combined synergistically with thermotherapy and chemotherapy, which has more significant anticancer effects than MTRN/DOX.

Neural stem cell transplants improve cognitive function without altering amyloid pathology in an APP/PS1 double transgenic model of Alzheimer's disease.

Neural stem cells (NSCs) are capable of self-renewal and are multipotent. Transplantation of NSCs may represent a promising approach for treating neurodegenerative disorders associated with cognitive decline, such as Alzheimer disease (AD) characterized by extensive loss of neurons. In this study, we investigated the effect of NSC transplantation on cognitive function in the amyloid precursor protein/presenilin-1 (APP/PS1) transgenic mouse, an AD mouse model with age-dependent cognitive deficits. We found that NSCs bilaterally transplanted into hippocampal regions improved spatial learning and memory function in these mice, but did not alter Aß pathology. Immunohistochemical analyses determined that NSCs proliferated, migrated, and differentiated into three neuronal cell types. The improvement in cognitive function was correlated with enhanced long-term potentiation (LTP) and an increase in the neuron expression of proteins related to cognitive function: N-methyl-D-aspartate (NMDA) 2B unit, synaptophysin (SYP), protein kinase C ζ subtypes (PKCζ), tyrosine receptor kinase B (TrkB), and brain-derived neurotrophic factor (BDNF). Taken together, our data indicated that injected NSCs can rescue cognitive deficits in APP/PS1 transgenic mice by replacing neuronal cell types expressing multiple cognition-related proteins that enhance LTP.

[In vivo labeling of rat neural progenitor cells in subventricular zone with superparamagnetic iron oxide for tracking of magnetic resonance imaging].

OBJECTIVE: To explore the feasibility of in vivo labeling of adult rat neural progenitor cells (NPCs) in subventricular zone (SVZ) with superparamagnetic iron oxide particles (SPIOs) for tracking of magnetic resonance imaging (MRI). METHODS: A total of 7 SD rats were stereotactically injected with 3 µl SPIOs (7 mg Fe/ml) into anterior horn of right lateral ventricle and then 5-bromo-2'-deoxyuridine (BrdU) was injected intraperitoneally once daily for 1 week. MRI was performed at 1, 3, 7 and 14 days post-injection. After the final MRI scan, all rats were transcardially perfused and their brains removed and fixed. The sections were processed for Prussian blue iron staining and Prussian blue plus BrdU immunohistochemical staining. RESULTS: In all experimental animals, SPIOs were predominantly located in the anterior horn of right lateral ventricle and partial SPIOs entered the ventricular system. A needle path and a distribution of SPIOs along rostral migratory stream (RMS) towards olfactory bulb (OB) were depicted at the sagittal view of T2(*)WI, moderate MR artifact was visible and SPIOs tracking NPCs were successful (success rate of 100%). The result of staining showed SPIOs labeling NPCs were effective. And the labeling rates were 75.5%, 42.3%, 23.6% in SVZ, RMS and OB respectively. CONCLUSION: Effective in vivo labeling of adult rat NPCs in SVZ with SPIOs is feasible. And dynamical migration of labeling NPCs along RMS towards OB may be visualized on MRI.

Silencing of the P2X(7) receptor enhances amyloid-ß phagocytosis by microglia.

P2X7 receptor (P2X7R) is an ATP-gated cation channel that promotes microglia activation and plays a critical role in the pathogenesis of Alzheimer's disease. Inhibiting P2X7R indirectly reduces the rate of amyloid-ß (Aß)-induced neurodegeneration by suppressing secretion of inflammatory factors from activated microglia. We used RNA interference to silence P2X7R in microglial cells in vitro and found it markedly increased microglial phagocytosis of Aß1-42. Increased phagocytic activity was dependent on decreasing the rate of interleukin-1ß release from microglia and required inhibition of the COX-2 pathway. Modulation of microglial phagocytosis and secretion via silencing P2X7R may be a promising therapeutic option for the treatment of Alzheimer's disease.

[Effects of RNA interference targeting P2X7 receptor on microglial phagocytosis of amyloid-ß protein].

OBJECTIVE: To investigate the effect of silencing P2X7 receptor (P2X7R) by RNA interference on microglial phagocytosis of amyloid-ß (Aß) protein and to explore its possible mechanism. METHODS: The small interfering RNA (siRNA) targeting the P2X7R gene was identified. The microglial cells activated by Aß1-42 were infected with the Lipofectamine-siP2X7R and it was designated as siP2X7R group. Microglia infected with Lipofectamine-siNC was designated as siNC group and non-infected cells as con group. The levels of P2X7R mRNA were detected by real-time PCR and the P2X7R protein was determined by Western blotting. The levels of IL-1ß and TNF-α were measured by ELISA. The microglial phagocytosis of Aß1-42 was observed by ELISA and immunocytochemistry staining. RESULTS: Detected by the Real-time PCR, the expression level of P2X7R mRNA of siP2X7R group decreased significantly versus siNC and con groups (P<0.05). The lowered expression of P2X7R protein detected by Western blotting was consistent with Real-time PCR. After RNA interference silencing P2X7R, the levels of IL-1ß and TNF-α detected by ELISA in siP2X7R group less than those in con, siNC groups, significantly (P<0.05). In con, siNC and siP2X7R groups respectively, the levels of Aß1-42 in supernatant were (423±20) pg/ml, (417±16) pg/ml, (296±30) pg/ml and the levels of Aß1-42 in the microglia were (190±37) pg/ml, (187±39) pg/ml, (322±26) pg/ml. Compared to siNC and con groups, in siP2X7R group the levels of Aß1-42 in supernatant decreased (P<0.05) and the levels of Aß1-42 in the microglia increased (P<0.05). Aß1-42 immunofluorescence staining showed that the red fluorescent products were seen in the cytoplasm of most microglias in siP2X7R group, but in con or siNC groups in only few microglias these products were depicted. CONCLUSIONS: The silence expression of P2X7R by RNA interference effectively decreases the levels of IL-1ß and TNF-α released by microglia and promotes microglia to phagocytose Aß. P2X7R could be used as an effective therapeutic target for RNA interference treatment of Alzheimer's disease.