Chest CT Patterns from Diagnosis to 1 Year of Follow-up in Patients with COVID-19.

Background The chest CT manifestations of COVID-19 from hospitalization to convalescence after 1 year are unknown. Purpose To assess chest CT manifestations of COVID-19 up to 1 year after symptom onset. Materials and Methods Patients were enrolled if they were admitted to the hospital because of COVID-19 and underwent CT during hospitalization at two isolation centers between January 27, 2020, and March 31, 2020. In a prospective study, three serial chest CT scans were obtained at approximately 3, 7, and 12 months after symptom onset and were longitudinally analyzed. The total CT score of pulmonary lobe involvement, ranging from 0 to 25, was assessed (score of 1-5 for each lobe). Univariable and multivariable logistic regression analyses were performed to explore independent risk factors for residual CT abnormalities after 1 year. Results A total of 209 study participants (mean age, 49 years ± 13 [standard deviation]; 116 women) were evaluated. CT abnormalities had resolved in 61% of participants (128 of 209) at 3 months and in 75% of participants (156 of 209) at 12 months. Among participants with chest CT abnormalities that had not resolved, there were residual linear opacities in 25 of the 209 participants (12%) and multifocal reticular or cystic lesions in 28 of the 209 participants (13%). Age 50 years or older, lymphopenia, and severe or aggravation of acute respiratory distress syndrome were independent risk factors for residual CT abnormalities at 1 year (odds ratios = 15.9, 18.9, and 43.9, respectively; P < .001 for each comparison). In 53 participants with residual CT abnormalities at 12 months, reticular lesions (41 of 53 participants [77%]) and bronchial dilation (39 of 53 participants [74%]) were observed at discharge and were persistent in 28 (53%) and 24 (45%) of the 53 participants, respectively. Conclusion One year after COVID-19 diagnosis, chest CT scans showed abnormal findings in 53 of the 209 study participants (25%), with 28 of the 209 participants (13%) showing subpleural reticular or cystic lesions. Older participants with severe COVID-19 or acute respiratory distress syndrome were more likely to develop lung sequelae that persisted at 1 year. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lee and Wi et al in this issue.

Impact of TIPS on Splenic Volume and Thrombocytopenia.

OBJECTIVE. Splenomegaly and thrombocytopenia are common complications in patients with cirrhosis. The present study aimed to evaluate changes in splenic volumes and platelet counts after TIPS insertion. MATERIALS AND METHODS. A total of 104 patients who had a diagnosis of portal hypertension and had undergone TIPS placement between November 2015 and August 2019 were enrolled in this retrospective cohort study. We retrospectively calculated splenic volumes before TIPS placement and at 1-2 and 6-12 months after TIPS placement and monitored the platelet count at 1, 3, 6, and 12 months after TIPS placement. RESULTS. The mean (± SD) portal pressure gradient before TIPS placement was 28.3 ± 4.6 mm Hg; after TIPS placement, it was 11.3 ± 4.5 mm Hg (p < .001). The mean splenic volume of all 104 patients before TIPS placement was 868 ± 409 cm3, and at 1-2 months after TIPS placement, it was 710 ± 336 cm3 (p < .001). Among the 43 patients for whom splenic volume data were available at both 1-2 and 6-12 months after TIPS placement, the mean splenic volume decreased from 845 ± 342 cm3 to 691 ± 301 cm3 and then to 674 ± 333 cm3, respectively. Correspondingly, the number of patients with severe thrombocytopenia decreased from 25 patients (35.7%) before the TIPS procedure to 16 patients (22.9%) in the 1-2 months after TIPS placement and then to 11 patients (15.7%) in the 6-12 months after TIPS implantation. The increase in the platelet count was significantly correlated with decreasing splenic volume (r2 = 0.3735; p < .001). CONCLUSION. In most patients, TIPS placement resulted in a significant decrease in splenic volume and a significant increase in the platelet count during the same period.

Radiomics Signature: A potential biomarker for the prediction of survival in Advanced Hepatocellular Carcinoma.

Objectives: To develop and validate radiomics nomograms for the pretreatment predictions of overall survival (OS) and time to progression (TTP) in the patients with advanced hepatocellular carcinoma (HCC) treated with apatinib plus transarterial chemoembolization (TACE), and to assess the incremental value of the clinical-radiomics nomograms for estimating individual OS and TTP. Methods: A total of 60 patients with advanced HCC (BCLC stage C) treated with apatinib plus TACE were divided into a training set (n=48) and a validation set (n=12). The predictors identified from the clinical variables and the radiomics signature constructed from the computed tomography images, such as ɑ-fetoprotein level (AFP), formfactor, the grey level co-occurrence matrix, the gray level size zone matrix, and the gray level run-length matrix, were used to build the clinical-radiomics nomograms and the radiomics nomograms for the prediction of OS and TTP. Results: Apatinib plus TACE benefited the patients with advanced HCC, with a 579-day median OS and a 270-day median TTP. The nomograms were built with the radiomics signature and AFP, and achieved favorable prediction efficacy with acceptable calibration curves. Decision curve analyses demonstrated that the clinical-radiomics nomograms outperformed the radiomics nomograms for the predictions of OS and TTP. Conclusions: Apatinib plus TACE may improve OS and prolonged TTP in the patients with advanced HCC. The clinical-radiomics nomograms, a noninvasive pretreatment prediction tool that incorporate radiomics signature and AFP, demonstrated good prediction accuracy for OS and TTP in these patients. These results indicate that the clinical-radiomics nomograms may provide novel insight for precise personalized medicine approaches in the patients with advanced HCC.

Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19).

Background Chest CT is used to assess the severity of lung involvement in coronavirus disease 2019 (COVID-19). Purpose To determine the changes in chest CT findings associated with COVID-19 from initial diagnosis until patient recovery. Materials and Methods This retrospective review included patients with real-time polymerase chain reaction-confirmed COVID-19 who presented between January 12, 2020, and February 6, 2020. Patients with severe respiratory distress and/or oxygen requirement at any time during the disease course were excluded. Repeat chest CT was performed at approximately 4-day intervals. Each of the five lung lobes was visually scored on a scale of 0 to 5, with 0 indicating no involvement and 5 indicating more than 75% involvement. The total CT score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement). Results Twenty-one patients (six men and 15 women aged 25-63 years) with confirmed COVID-19 were evaluated. A total of 82 chest CT scans were obtained in these patients, with a mean interval (±standard deviation) of 4 days ± 1 (range, 1-8 days). All patients were discharged after a mean hospitalization period of 17 days ± 4 (range, 11-26 days). Maximum lung involved peaked at approximately 10 days (with a calculated total CT score of 6) from the onset of initial symptoms (R2 = 0.25, P < .001). Based on quartiles of chest CT scans from day 0 to day 26 involvement, four stages of lung CT findings were defined. CT scans obtained in stage 1 (0-4 days) showed ground-glass opacities (18 of 24 scans [75%]), with a mean total CT score of 2 ± 2; scans obtained in stage 2 (5-8 days) showed an increase in both the crazy-paving pattern (nine of 17 scans [53%]) and total CT score (mean, 6 ± 4; P = .002); scans obtained in stage 3 (9-13 days) showed consolidation (19 of 21 scans [91%]) and a peak in the total CT score (mean, 7 ± 4); and scans obtained in stage 4 (≥14 days) showed gradual resolution of consolidation (15 of 20 scans [75%]) and a decrease in the total CT score (mean, 6 ± 4) without crazy-paving pattern. Conclusion In patients recovering from coronavirus disease 2019 (without severe respiratory distress during the disease course), lung abnormalities on chest CT scans showed greatest severity approximately 10 days after initial onset of symptoms. © RSNA, 2020.

Identification and validation of stromal-tumor microenvironment-based subtypes tightly associated with PD-1/PD-L1 immunotherapy and outcomes in patients with gastric cancer.

BACKGROUND: Immunotherapies targeting programmed cell death 1 (PD-1) and programmed death-ligand 1 (PD-L1) have been approved for gastric cancer (GC) patients. However, a large proportion of patients with T-cell-inflamed tumor microenvironment do not respond to the PD-1/PD-L1 blockade. The stromal component of the tumor microenvironment has been associated with immunotherapy. This study aims to explore the clinical significance of the non-immune cells in the tumor microenvironment and their potential as biomarkers for immunotherapy. METHODS: A total of 383 patients with GC from the Cancer Genome Atlas (TCGA) cohort, 300 patients with GC from the GSE62254 cohort in Gene Expression Omnibus (GEO) were included in the study. A stromal score was generated using the ESTIMATE algorithm, and the likelihood of response to PD-1/PD-L1 immunotherapy of GC patients was predicted using the TIDE algorithm. The prognostic value of the stromal score from GC cases was evaluated by the Kaplan-Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was also conducted. RESULTS: The stromal score showed significant differences in different molecular subtypes and T stages. Multivariate analyses further confirmed that the stromal score was an independent indicator of overall survival (OS) in the two cohorts. The low stromal score group showed higher tumor mutation burden (TMB) and micro-satellite instability (MSI), and was more sensitive to immune checkpoint inhibitor according to the TIDE algorithm. Activation of the transforming growth factor and epithelial-mesenchymal transition were observed in the high stromal score subtype, which is associated with T-cell suppression, and may be responsible for resistance to PD-1/PD-L1 therapy. BPIFB2 was confirmed as a hub gene relevant to immunotherapy. CONCLUSION: The stromal score was associated with cancer progression and molecular subtypes, and may serve as a novel biomarker for predicting the prognosis and response to immunotherapy in patients with GC.

Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study.

Rationale: Up to date, the exploration of clinical features in severe COVID-19 patients were mostly from the same center in Wuhan, China. The clinical data in other centers is limited. This study aims to explore the feasible parameters which could be used in clinical practice to predict the prognosis in hospitalized patients with severe coronavirus disease-19 (COVID-19). Methods: In this case-control study, patients with severe COVID-19 in this newly established isolation center on admission between 27 January 2020 to 19 March 2020 were divided to discharge group and death event group. Clinical information was collected and analyzed for the following objectives: 1. Comparisons of basic characteristics between two groups; 2. Risk factors for death on admission using logistic regression; 3. Dynamic changes of radiographic and laboratory parameters between two groups in the course. Results: 124 patients with severe COVID-19 on admission were included and divided into discharge group (n=35) and death event group (n=89). Sex, SpO2, breath rate, diastolic pressure, neutrophil, lymphocyte, C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), and D-dimer were significantly correlated with death events identified using bivariate logistic regression. Further multivariate logistic regression demonstrated a significant model fitting with C-index of 0.845 (p<0.001), in which SpO2≤89%, lymphocyte≤0.64×109/L, CRP>77.35mg/L, PCT>0.20µg/L, and LDH>481U/L were the independent risk factors with the ORs of 2.959, 4.015, 2.852, 3.554, and 3.185, respectively (p<0.04). In the course, persistently lower lymphocyte with higher levels of CRP, PCT, IL-6, neutrophil, LDH, D-dimer, cardiac troponin I (cTnI), brain natriuretic peptide (BNP), and increased CD4+/CD8+ T-lymphocyte ratio and were observed in death events group, while these parameters stayed stable or improved in discharge group. Conclusions: On admission, the levels of SpO2, lymphocyte, CRP, PCT, and LDH could predict the prognosis of severe COVID-19 patients. Systematic inflammation with induced cardiac dysfunction was likely a primary reason for death events in severe COVID-19 except for acute respiratory distress syndrome.

Abnormal brain structure as a potential biomarker for venous erectile dysfunction: evidence from multimodal MRI and machine learning.

OBJECTIVES: To investigate the cerebral structural changes related to venous erectile dysfunction (VED) and the relationship of these changes to clinical symptoms and disorder duration and distinguish patients with VED from healthy controls using a machine learning classification. METHODS: 45 VED patients and 50 healthy controls were included. Voxel-based morphometry (VBM), tract-based spatial statistics (TBSS) and correlation analyses of VED patients and clinical variables were performed. The machine learning classification method was adopted to confirm its effectiveness in distinguishing VED patients from healthy controls. RESULTS: Compared to healthy control subjects, VED patients showed significantly decreased cortical volumes in the left postcentral gyrus and precentral gyrus, while only the right middle temporal gyrus showed a significant increase in cortical volume. Increased axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) values were observed in widespread brain regions. Certain regions of these alterations related to VED patients showed significant correlations with clinical symptoms and disorder durations. Machine learning analyses discriminated patients from controls with overall accuracy 96.7%, sensitivity 93.3% and specificity 99.0%. CONCLUSIONS: Cortical volume and white matter (WM) microstructural changes were observed in VED patients, and showed significant correlations with clinical symptoms and dysfunction durations. Various DTI-derived indices of some brain regions could be regarded as reliable discriminating features between VED patients and healthy control subjects, as shown by machine learning analyses. KEY POINTS: • Multimodal magnetic resonance imaging helps clinicians to assess patients with VED. • VED patients show cerebral structural alterations related to their clinical symptoms. • Machine learning analyses discriminated VED patients from controls with an excellent performance. • Machine learning classification provided a preliminary demonstration of DTI's clinical use.

Exploring the effects of calycosin on anthracycline-induced cardiotoxicity: a network pharmacology, molecular docking, and experimental study.

Background: Chemotherapy with anthracyclines can cause cardiotoxicity, possibly leading to stopping treatment in some cancer patients. In cardio-oncology research, preventing and minimizing anthracycline-induced cardiotoxicity (AIC) is a hot issue. For the treatment of AIC, calycosin (CA), an isoflavone component in astragali radix (AR), has become a research focus. However, the elaborate mechanisms of calycosin treating AIC remain to be unrevealed. Aim of the study: To explore the effects of CA on AIC through multiple dimensions concerning network pharmacology, molecular docking, and experimental evaluations. Methods: The study evaluated calycosin's potential targets and mechanisms for treating AIC using network pharmacology and molecular docking. The candidate genes/targets of CA and AIC were screened using the online-available database. Protein-protein interactions (PPI) between the common targets were constructed using the STRING platform, and the results were then visualized using Cytoscape. Molecular docking was used to evaluate the strength of the binding force between CA and the common targets. The possible pharmacological mechanisms of CA were explained by pathway enrichment and GSEA. Subsequently, the candidate targets were identified in vitro experiments. Results: Network pharmacology effectively discovered the CA's multitarget intervention in AIC, including TNF, ABCC1, TOP2A, ABCB1, and XDH. CA binds to the ATP-binding cassette subfamily B member 1(ABCB1) had the highest binding energy (-7.5 kcal/mol) according to the molecular docking analysis and was selected and visualized for subsequent analysis. In vitro experiments showed that ABCB1 exhibited significant time-curve changes under different doses of doxorubicin (DOX) compared with DMSO control experiments. The anti-AIC pharmacological mechanism of CA were revealed by highlighting the biological processes of oxidative stress (OR) and inflammation. Conclusions: We employed a practicable bioinformatics method to connect network and molecular docking to determine the calycosin's therapeutic mechanism against AIC and identified some bioinformatics results in in vitro experiments. The results presented show that CA may represent an encouraging treatment for AIC.

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients.

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

A gadoxetic-acid enhancement flux analysis of small liver nodules (≤2 cm) in patients at high risk of hepatocellular carcinoma.

PURPOSE: To discriminate between benignities and hepatocellular carcinomas (HCCs) in patients at high risk of HCC using a novel enhancement flux analysis for gadoxetic-acid enhanced MRI. METHOD: This study retrospectively collected 181 liver nodules in 156 patients at high risk of HCC who underwent gadoxetic acid-enhanced MRI examinations with following surgical resection from 1st August 2017 to 31st December 2021 as the training set; another 42 liver nodules in 36 patients were prospectively collected from 1st January 2022 to 1st October 2022 as the test set. The time-intensity curves (TICs) of liver nodules were formed with consecutive time points: 0 s, 20 s, 1 min, 2 min, 5 min, 10 min, 15 min, and 20 min since contrast injection. A novel enhancement flux analysis was applied by using a biexponential function fitting to distinguish benignities and HCC. Besides, previously published models including maximum enhancement ratio (ERmax), percentage signal ratio (PSR), and ERmax+PSR were compared. The areas under the receiver operating characteristic curves (AUCs) were compared among these methods. RESULTS: The novel enhancement flux analysis showed the highest AUCs in the training set (0.897, 95%CI: 0.833-0.960) and the test set (0.859, 95%CI: 0.747-0.970) among all models. The AUCs of PSR, ERmax and ERmax+PSR were 0.801 (95%CI: 0.710-0.891), 0.620 (95%CI: 0.510-0.729), and 0.799 (95%CI: 0.709-0.889) in the training set, and were 0.701 (95%CI: 0.539-0.863), 0.529 (95%CI: 0.342-0.717), and 0.708 (95%CI: 0.549-0.867) in the test set. CONCLUSIONS: The biexponential flux analysis for gadoxetic-acid enhanced MRI presents a better potential in accurate diagnosis of small HCC nodules.

A semiautomated radiomics model based on multimodal dual-layer spectral CT for preoperative discrimination of the invasiveness of pulmonary ground-glass nodules.

Background: In recent years, spectral computed tomography (CT) has shown excellent performance in the diagnosis of ground-glass nodules (GGNs) invasiveness; however, no research has combined spectral multimodal data and radiomics analysis for comprehensive analysis and exploration. Therefore, this study goes a step further on the basis of the previous research: to investigate the value of dual-layer spectral CT-based multimodal radiomics in accessing the invasiveness of lung adenocarcinoma manifesting as GGNs. Methods: In this study, 125 GGNs with pathologically confirmed preinvasive adenocarcinoma (PIA) and lung adenocarcinoma were divided into a training set (n=87) and a test set (n=38). Each lesion was automatically detected and segmented by the pre-trained neural networks, and 63 multimodal radiomic features were extracted. The least absolute shrinkage and selection operator (LASSO) was used to select target features, and a rad-score was constructed in the training set. Logistic regression analysis was conducted to establish a joint model which combined age, gender, and the rad-score. The diagnostic performance of the two models was compared by the receiver operating characteristic (ROC) curve and precision-recall curve. The difference between the two models was compared by the ROC analysis. The test set was used to evaluate the predictive performance and calibrate the model. Results: Five radiomic features were selected. In the training and test sets, the area under the curve (AUC) of the radiomics model was 0.896 (95% CI: 0.830-0.962) and 0.881 (95% CI: 0.777-0.985) respectively, and the AUC of the joint model was 0.932 (95% CI: 0.882-0.982) and 0.887 (95% CI: 0.786-0.988) respectively. There was no significant difference in AUC between the radiomics model and joint model in the training and test sets (0.896 vs. 0.932, P=0.088; 0.881 vs. 0.887, P=0.480). Conclusions: Multimodal radiomics based on dual-layer spectral CT showed good predictive performance in differentiating the invasiveness of GGNs, which could assist in the decision of clinical treatment strategies.

Application and development of Deuterium Metabolic Imaging in tumor glucose metabolism: visualization of different metabolic pathways.

Cancer metabolism has emerged as a pivotal area of research recently. The ability to visualize and comprehend the metabolic processes of cancer holds immense clinical value, particularly in the diagnosis of malignant tumors and the assessment of treatment responses. Deuterium Metabolic Imaging (DMI), as a robust, simple, and versatile MR spectroscopic imaging tool, demonstrates promise in tumor diagnosis and treatment efficacy assessment. This review explored the latest developments and applications of DMI in oncology across various tumor metabolic axes, with a specific emphasis on its potential for clinical translation. DMI offers invaluable insights into tumor biology, treatment responses, and prognostic outcomes. Notably, DMI can identify early responses to immunotherapy, a prominent area of current research interest. In conclusion, DMI harbors the potential to evolve into a convenient and efficient imaging technique in clinical practice, thereby advancing precision medicine and improving the diagnosis and evaluation of cancer treatments.

Liver abscess after drug-eluting bead chemoembolization in patients with metastatic hepatic tumors.

OBJECTIVE: To investigate the incidence and risk factors for liver abscess formation after treatment with drug-eluting bead chemoembolization (DEB-TACE) in patients with metastatic hepatic tumors (MHT). METHODS: The current study is a retrospective analysis of the clinical data of 137 patients with metastatic hepatic tumors who received DEB-TACE treatment in our institute (Union Hospital, Tongji Medical College, Huazhong University of Science and Technology) between June 2015 and September 2020. Patients were evaluated for the presence or absence of post-DEB-TACE liver abscess. Univariate and multivariate analyses were used to identify risk factors for liver abscess formation. RESULTS: The incidence of liver abscess formation after the DEB-TACE procedure was 8.76% per patient and 5.53% per procedure. Univariate analysis showed that larger maximum tumor diameter (p = 0.004), Grade 1 artery occlusion (p < 0.001) and systemic chemotherapy within 3 months before the DEB-TACE procedure (p < 0.001) were all associated with liver abscess formation. However, only systemic chemotherapy within 3 months before the DEB-TACE procedure (OR 5.49; 95% CI 0.34-13.54; p < 0.001) was identified by multivariate analysis to be an independent risk factor. CONCLUSIONS: Tumor size, Grade 1 artery occlusion and recent systemic chemotherapy may all be associated with increased risk of liver abscess formation following DEB-TACE treatment in patients with metastatic hepatic tumors. ADVANCES IN KNOWLEDGE: Identification of risk factors for liver abscess formation following DEB-TACE in patients with MHT. These findings suggest the need for caution and consideration of the aforementioned risk factors on the part of interventional radiologists when designing DEB-TACE strategies and performing post-procedure patient management.

Evaluation of dangerous collateral vessels and thrombus in Budd-Chiari syndrome patients with inferior vena cava obstruction.

PURPOSE: To evaluate the diagnostic accuracy of preoperative imaging in defining inferior vena cava (IVC) obstruction characteristics, in identifying the presence of a thrombus and dangerous venous collateral. The other goal is to explore the clinical implication of these data in the designing the treatment strategy in Budd-Chiari patients. METHODS: This study included 112 patients with IVC obstruction who underwent endovascular treatment between July 2009 and June 2019. Two radiologists independently assessed MSCT and/or MRI imaging data with a 5-point scale to evaluate the diagnostic accuracies relating to obstructive characteristics, dangerous collateral vessels, and thrombus within IVC. RESULTS: The diagnostic sensitivities for obstructive characteristics, as determined by the two independent assessors, ranged from 81.25 to 100%. The areas under the receiver operating characteristic curve (ROC) for judging thrombus ranged from 0.87 to 0.975 for the two assessors. Inter-assessor agreement was substantial or excellent with regards to diagnostic accuracy (κ = 0.745-0.927). Twelve cases involving dangerous collateral vessels were identified in the MSCT group of 82 patients (κ = 1); six were identified by digital subtraction venography (DSV) imaging. Eight cases involving dangerous collateral vessels were reported in the MRI group of 32 patients (κ = 1); three were identified by DSV imaging. CONCLUSION: Preoperative MSCT and MRI can accurately reveal the obstructive characteristics and risk factors of patients with IVC obstruction and can therefore be used to guide interventional planning so as to minimize complications.

A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19).

This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: (1) Correlation between these two estimations; (2) Exploring the dynamic patterns using these two estimations between moderate and severe groups. The Spearman's correlation coefficient between these two estimation methods was 0.920 (p < 0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.

Sublethal hyperthermia enhances anticancer activity of doxorubicin in chronically hypoxic HepG2 cells through ROS-dependent mechanism.

Thermal ablation in combination with transarterial chemoembolization (TACE) has been reported to exert a more powerful antitumor effect than thermal ablation alone in hepatocellular carcinoma patients. However, the underlying mechanisms remain unclear. The purpose of the present study was to evaluate whether sublethal hyperthermia encountered in the periablation zone during thermal ablation enhances the anticancer activity of doxorubicin in chronically hypoxic (encountered in the tumor area after TACE) liver cancer cells and to explore the underlying mechanisms. In the present study, HepG2 cells precultured under chronic hypoxic conditions (1% oxygen) were treated in a 42°C water bath for 15 or 30 min, followed by incubation with doxorubicin. Assays were then performed to determine intracellular uptake of doxorubicin, cell viability, apoptosis, cell cycle, mitochondrial membrane potential (MMP), reactive oxygen species (ROS), and total antioxidant capacity. The results confirmed that sublethal hyperthermia enhanced the intracellular uptake of doxorubicin into hypoxic HepG2 cells. Hyperthermia combined with doxorubicin led to a greater inhibition of cell viability and increased apoptosis in hypoxic HepG2 cells as compared with hyperthermia or doxorubicin alone. In addition, the combination induced apoptosis by increasing ROS and causing disruption of MMP. Pretreatment with the ROS scavenger N-acetyl cysteine significantly inhibited the apoptotic response, suggesting that cell death is ROS-dependent. These findings suggested that sublethal hyperthermia enhances the anticancer activity of doxorubicin in hypoxic HepG2 cells via a ROS-dependent mechanism.

Management of isolated dissection of the abdominal aorta: a single-centre experience.

OBJECTIVES: Isolated abdominal aortic dissection (IAAD) is a rare disease. Currently, there is no consensus on the management of IAAD. Our goal was to report our experience with the management of IAAD. METHODS: A cohort of 45 consecutive patients with IAAD was treated between January 2010 and December 2018. We reviewed the demographics, clinical features, therapeutic modalities and follow-up results. RESULTS: A total of 33 patients had successful endovascular repair (EVAR) and 12 patients underwent conservative treatment initially. During a mean follow-up of 16.6 months, 2 of the patients in the EVAR group had endoleak; neither of them needed reintervention. Complete or partial thrombosis of the false lumens was seen in all patients (88% and 12%) on the latest computed tomographic angiography images, and a significant enlargement of the true lumen and regression of the false lumen and maximal abdominal aortic diameter were observed in all patients (P < 0.001). In the group receiving conservative treatment, 3 patients were lost to follow-up; 1 patient died; 2 patients had small re-entry sites, neither of which needed intervention; 1 patient had EVAR; and the others remain symptom-free. The latest computed tomographic angiography images showed that 1 patient had spontaneous healing with complete thrombosis of the false lumen, 7 patients had partial thrombosis and the diameter of the maximal abdominal aortic and false lumen remained stable or was less decreased. CONCLUSIONS: For patients with IAAD, close surveillance is necessary. In addition, EVAR is an effective therapeutic method with a high technical success rate and low complication rate for carefully selected patients.

NRF2/ABCB1-mediated efflux and PARP1-mediated dampening of DNA damage contribute to doxorubicin resistance in chronic hypoxic HepG2 cells.

Transarterial chemoembolization (TACE)-induced hypoxia can trigger residual liver cancer cells to present a more aggressive phenotype associated with chemoresistance, but the underlying mechanisms are still unknown. In this study, the human liver cancer cell line HepG2 was pre-cultured in different oxygen environments to examine the possible mechanisms of hypoxia-induced doxorubicin resistance. Our study showed that HepG2 cells pre-cultured in a chronic intermittent hypoxic environment exhibited significant resistance to doxorubicin, evidenced by increased intracellular doxorubicin efflux, relatively higher cell proliferation, lower apoptosis, and decreased DNA damage. These changes were accompanied by high levels of NRF2 and ABCB1 under conditions of both chronic and acute hypoxia and PARP1 gene expression only under conditions of chronic hypoxia. SiRNA-mediated silencing of NRF2 gene expression downregulated the expression of ABCB1 and increased the intracellular doxorubicin accumulation and cell apoptosis both in acute and chronic hypoxic HepG2 cells. Moreover, silencing of PARP1 gene expression increased the doxorubicin-induced DNA damage and cell apoptosis in chronic hypoxic cells. On the basis of these findings, we concluded that NRF2/ABCB1-mediated efflux and PARP1-mediated DNA repair contribute to doxorubicin resistance in chronic hypoxic HepG2 cells.

Different computed tomography patterns of Coronavirus Disease 2019 (COVID-19) between survivors and non-survivors.

This study aimed to compare the chest computed tomography (CT) findings between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19). Between 12 January 2020 and 20 February 2020, the records of 124 consecutive patients diagnosed with COVID-19 were retrospectively reviewed and divided into survivor (83/124) and non-survivor (41/124) groups. Chest CT findings were qualitatively compared on admission and serial chest CT scans were semi-quantitively evaluated between two groups using curve estimations. On admission, significantly more bilateral (97.6% vs. 73.5%, p = 0.001) and diffuse lesions (39.0% vs. 8.4%, p < 0.001) with higher total CT score (median 10 vs. 4, p < 0.001) were observed in non-survivor group compared with survivor group. Besides, crazy-paving pattern was more predominant in non-survivor group than survivor group (39.0% vs. 12.0%, p < 0.001). From the prediction of curve estimation, in survivor group total CT score increased in the first 20 days reaching a peak of 6 points and then gradually decreased for more than other 40 days (R2 = 0.545, p < 0.001). In non-survivor group, total CT score rapidly increased over 10 points in the first 10 days and gradually increased afterwards until ARDS occurred with following death events (R2 = 0.711, p < 0.001). In conclusion, persistent progression with predominant crazy-paving pattern was the major manifestation of COVID-19 in non-survivors. Understanding this CT feature could help the clinical physician to predict the prognosis of the patients.