Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagnostic study.

OBJECTIVES: To develop and validate a preoperative CT-based nomogram combined with radiomic and clinical-radiological signatures to distinguish preinvasive lesions from pulmonary invasive lesions. METHODS: This was a retrospective, diagnostic study conducted from August 1, 2018, to May 1, 2020, at three centers. Patients with a solitary pulmonary nodule were enrolled in the GDPH center and were divided into two groups (7:3) randomly: development (n = 149) and internal validation (n = 54). The SYSMH center and the ZSLC Center formed an external validation cohort of 170 patients. The least absolute shrinkage and selection operator (LASSO) algorithm and logistic regression analysis were used to feature signatures and transform them into models. RESULTS: The study comprised 373 individuals from three independent centers (female: 225/373, 60.3%; median [IQR] age, 57.0 [48.0-65.0] years). The AUCs for the combined radiomic signature selected from the nodular area and the perinodular area were 0.93, 0.91, and 0.90 in the three cohorts. The nomogram combining the clinical and combined radiomic signatures could accurately predict interstitial invasion in patients with a solitary pulmonary nodule (AUC, 0.94, 0.90, 0.92) in the three cohorts, respectively. The radiomic nomogram outperformed any clinical or radiomic signature in terms of clinical predictive abilities, according to a decision curve analysis and the Akaike information criteria. CONCLUSIONS: This study demonstrated that a nomogram constructed by identified clinical-radiological signatures and combined radiomic signatures has the potential to precisely predict pathology invasiveness. KEY POINTS: • The radiomic signature from the perinodular area has the potential to predict pathology invasiveness of the solitary pulmonary nodule. • The new radiomic nomogram was useful in clinical decision-making associated with personalized surgical intervention and therapeutic regimen selection in patients with early-stage non-small-cell lung cancer.

Multi-instance learning based lung nodule system for assessment of CT quality after small-field-of-view reconstruction.

Small-field-of-view reconstruction CT images (sFOV-CT) increase the pixel density across airway structures and reduce partial volume effects. Multi-instance learning (MIL) is proposed as a weakly supervised machine learning method, which can automatically assess the image quality. The aim of this study was to evaluate the disparities between conventional CT (c-CT) and sFOV-CT images using a lung nodule system based on MIL and assessments from radiologists. 112 patients who underwent chest CT were retrospectively enrolled in this study between July 2021 to March 2022. After undergoing c-CT examinations, sFOV-CT images with small-field-of-view were reconstructed. Two radiologists analyzed all c-CT and sFOV-CT images, including features such as location, nodule type, size, CT values, and shape signs. Then, an MIL-based lung nodule system objectively analyzed the c-CT (c-MIL) and sFOV-CT (sFOV-MIL) to explore their differences. The signal-to-noise ratio of lungs (SNR-lung) and contrast-to-noise ratio of nodules (CNR-nodule) were calculated to evaluate the quality of CT images from another perspective. The subjective evaluation by radiologists showed that feature of minimal CT value (p = 0.019) had statistical significance between c-CT and sFOV-CT. However, most features (all with p < 0.05), except for nodule type, location, volume, mean CT value, and vacuole sign (p = 0.056-1.000), had statistical differences between c-MIL and sFOV-MIL by MIL system. The SNR-lung between c-CT and sFOV-CT had no statistical significance, while the CNR-nodule showed statistical difference (p = 0.007), and the CNR of sFOV-CT was higher than that of c-CT. In detecting the difference between c-CT and sFOV-CT, features extracted by the MIL system had more statistical differences than those evaluated by radiologists. The image quality of those two CT images was different, and the CNR-nodule of sFOV-CT was higher than that of c-CT.

Heart-on-a-chip systems with tissue-specific functionalities for physiological, pathological, and pharmacological studies.

Recent advances in heart-on-a-chip systems hold great promise to facilitate cardiac physiological, pathological, and pharmacological studies. This review focuses on the development of heart-on-a-chip systems with tissue-specific functionalities. For one thing, the strategies for developing cardiac microtissues on heart-on-a-chip systems that closely mimic the structures and behaviors of the native heart are analyzed, including the imitation of cardiac structural and functional characteristics. For another, the development of techniques for real-time monitoring of biophysical and biochemical signals from cardiac microtissues on heart-on-a-chip systems is introduced, incorporating cardiac electrophysiological signals, contractile activity, and biomarkers. Furthermore, the applications of heart-on-a-chip systems in intelligent cardiac studies are discussed regarding physiological/pathological research and pharmacological assessment. Finally, the future development of heart-on-a-chip toward a higher level of systematization, integration, and maturation is proposed.

Empirical Compression Model of Ultra-High-Performance Concrete Considering the Effect of Cement Hydration on Particle Packing Characteristics.

The mix design of UHPC has always been based on a large number of experiments; in order to reduce the number of repeated experiments, in this study, silica fume (SF), fly ash (FA), and limestone powder (LP) were used as the raw materials to conduct 15 groups of experiments to determine the particle size distribution (PSD) properties of UHPC. A model of multi-component hydration based on the SF, FA, and LP pozzolanic reactions was devised to quantify the rate and total heat release during the hydration process. Additionally, a microscopic pore development model, which was based on the accumulation of hydration products, was established to measure the effect of these products on the particle-packing properties. Utilizing this model, a UHPC strength prediction technique was formulated to precisely forecast the compressive strength based on a restricted experimental data set. The applicability of this prediction method was verified using 15 sets of existing experimental data along with the data collected from 4 research articles. The results show that the prediction method can predict the strength values of different mix proportions with an accuracy rate of over 80%.

Predicting the WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma Through CT-Based Tumoral and Peritumoral Radiomics.

OBJECTIVES: This study aims to establish predictive logistic models for the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grades of clear cell renal cell carcinoma (ccRCC) based on tumoral and peritumoral radiomics. METHODS: A cohort of 370 patients with pathologically confirmed ccRCCs were included in this retrospective study between January 2014 and December 2020 according to the WHO/ISUP grading system. The volume of interests of triphasic computed tomography images were depicted manually using the "itk-SNAP" software, and the radiomics features were calculated. The cohort was segmented into the training cohort and validation cohort with a random proportion of 7:3. After extraction of radiomics features by analysis of variance (ANOVA) or Mann-Whitney U test, correlation analysis, and the least absolute shrinkage and selection operator (LASSO) method, the logistic models of tumoral radiomics (LR-tumor) and peritumoral radiomics (LR-peritumor) were developed. The LR-peritumor was subdivided into LR-peritumor-2mm, LR-peritumor-5mm, and LR-peritumor-10mm, and the LR-peritumor-2mm was subdivided into LR-peritumor-kid and LR-peritumor-fat based on the neighboring tissues of ccRCCs. Finally, an integrative model of tumoral and peritumoral radiomics (LR-tumor/peritumor) was built. The value of areas under the receiver operator characteristics curve (AUCs) was calculated to assess the efficacy of the models. RESULTS: There were 209 low-grade and 161 high-grade ccRCCs enrolled. The AUCs of LR-tumor in CT images of venous phase were 0.802 in the training cohort and 0.796 in the validation cohort. The AUCs were higher in the LR-peritumor-2mm than those in LR-peritumor-5mm and LR-peritumor-10mm (training cohort: 0.788 vs. 0.788 and 0.759; validation cohort: 0.787 vs. 0.785 and 0.758). Moreover, the AUCs of LR-peritumor-fat were higher compared with those of LR-peritumor-kid. The LR-tumor/peritumor displayed the highest AUCs of 0.812 in the training cohort and 0.804 in the validation cohort. CONCLUSIONS: The tumoral and peritumoral radiomics helped to predict the WHO/ISUP grades of ccRCCs. On the diagnostic performance of peritumoral radiomics, better results were seen for the LR-peritumor-2mm and LR-peritumor-fat.

A novel computed tomography radiomic nomogram for early evaluation of small airway dysfunction development.

The common respiratory abnormality, small airway dysfunction (fSAD), is easily neglected. Its prognostic factors, prevalence, and risk factors are unclear. This study aimed to explore the early detection of fSAD using radiomic analysis of computed tomography (CT) images to predict fSAD progress. The patients were divided into fSAD and non-fSAD groups and divided randomly into a training group (n = 190) and a validation group (n = 82) at a 7:3 ratio. Lung kit software was used for automatic delineation of regions of interest (ROI) on chest CT images. The most valuable imaging features were selected and a radiomic score was established for risk assessment. Multivariate logistic regression analysis showed that age, radiomic score, smoking, and history of asthma were significant predictors of fSAD (P < 0.05). Results suggested that the radiomic nomogram model provides clinicians with useful data and could represent a reliable reference to form fSAD clinical treatment strategies.

Pulmonary MALT lymphoma: Imaging findings in 18 cases and the associated pathological correlations.

BACKGROUND: Pulmonary MALT lymphoma is a rare disease that is easily misdiagnosed. The objective of this study was to improve the understanding of pulmonary MALT lymphoma for clinicians. METHODS: The computed tomography (CT) scans of 18 patients (13 males and 5 females), aged 41-70 years (mean=55.6 years), with histologically proven pulmonary MALT lymphoma were retrospectively reviewed by two radiologists, and pulmonary imaging findings were described. Correlations between the pulmonary abnormalities and histopathological findings in 13 patients were retrospectively reviewed. RESULTS: Elementary lesions were characterized by masses or mass-like areas of consolidation (15/18), nodules (5/18), air bronchograms (16/18), airway dilatation (7/18), cavitation (5/18), airways passing through the lesion (8/18), CT angiogram signs (12/14) and vessels passing through the lesion (12/14). Additional findings included multiple cysts (n = 1), pleural effusion (n = 1) and atelectasis (n = 1). Pulmonary abnormalities were correlated with pathological appearance. Pathological examination confirmed lymphomatous infiltration with a bronchovascular distribution but no vessel or airway destruction, which appeared on CT as the vessels/airways passed through lesions naturally. CONCLUSIONS: We herein demonstrated the imaging findings for 18 cases of pulmonary MALT lymphomas by analyzing the corresponding pathologies. We also discovered that vessels/airways could pass through pulmonary MALT lymphoma lesions, which may be helpful for diagnosis. This disease should be considered when chest CT imaging shows multiple/single masses or nodules or mass-like areas of consolidation together with vessels/airways passing through lesions.

Wogonin reverses the drug resistance of chronic myelogenous leukemia cells to imatinib through CXCL12-CXCR4/7 axis in bone marrow microenvironment.

BACKGROUND: In the current study, chronic myeloid leukemia (CML) cells (K562 and KU812) co-cultured with human bone marrow stromal cells (BMSCs) were significantly less sensitive to imatinib (IM). The activation of the CXCL12-CXCR4/7 axis plays an important role in the protective effect of the bone marrow microenvironment (BME) on CML cells. The aim of this study was to investigate whether Wogonin could increase the sensitivity of CML cells to IM when they were co-cultured with BME and explore its underlying mechanism. METHODS: A model of CML cells co-cultured with BMSCs was applied in vitro. Flow cytometric, western blotting, immunofluorescence, and RT-PCR assays were used to explore the protective effects of BME on CML cells. RESULTS: The results showed that Wogonin could reverse the resistance of CML cells to IM under co-culture conditions by inhibiting Transforming growth factor-ß (TGF-ß) secretion in the BME, preventing the translocation of Smad4 into nucleus and subsequently reducing the expression of CXCR4 and CXCR7 in CML cells. Moreover, the reverse effect of Wogonin was demonstrated by inhibiting the activation of CXCL12-CXCR4/7 axis via restraining the TGF-ß/Smad4/Id3 pathway in vitro. In vivo studies also showed that Wogonin decreased the expression of CXCR4 and CXCR7 in mice bone marrow with low systemic toxicity, and the mechanism was consistent with the in vitro study. CONCLUSIONS: Wogonin increases the sensitivity of CML cells to IM in BME by controlling the TGF-ß/Smad4/Id3 pathway and decreasing the expression of CXCR4 and CXCR7. These results co-supported the point that Wogonin could be a potential candidate of reversal agents on treatment of IM-resistant CML.

Oroxylin a Inhibits the Protection of Bone Marrow Microenvironment on CML Cells Through CXCL12/CXCR4/P-gp Signaling Pathway.

Imatinib (IM) resistance could have significant impact on the survival time of the CML-patients treated with IM. Previous studies have shown that the protective effects of the bone marrow stroma cells (BMSCs) on CML cells are achieved by the secretion of CXCL12. The aim of this study was to investigate whether Oroxylin A could reverse the protective effect of BMSCs on CML cells and illuminate the underlying mechanisms. The results showed that CXCL12 could enhance the resistance potential of K562 and KU812 cells to IM by increasing the expression of CXCR4, thus promoting the translocation of ß-catenin into nucleus and subsequently increasing the expression of P-gp in K562 and KU812 cells. What's more, IM resistance could also be partially reversed by CXCR4 siRNA transfection. Moreover, the reverse effect of IM resistance by Oroxylin A was demonstrated by the inhibition of ß-catenin/P-gp pathway via the decrease of CXCR4 in vitro. The in vivo study also showed that Oroxylin A could decrease the expression of P-gp and ß-catenin in mice bone marrow with low toxicity, which could be consistent with the mechanisms verified in vitro studies. In conclusion, all these results showed that Oroxylin A improved the sensitivity of K562 and KU812 cells to IM in BM microenvironment by decreasing the expression of CXCR4 and then inhibiting ß-catenin/P-gp pathway.

Corrigendum: Oroxylin a Inhibits the Protection of Bone Marrow Microenvironment on CML Cells Through CXCL12/CXCR4/P-gp Signaling Pathway.

[This corrects the article DOI: 10.3389/fonc.2019.00188.].

The CXCL12 (SDF-1)/CXCR4 chemokine axis: Oncogenic properties, molecular targeting, and synthetic and natural product CXCR4 inhibitors for cancer therapy.

Chemokine 12 (CXCL12), also known as stromal cell derived factor-1 (SDF-1) and a member of the CXC chemokine subfamily, is ubiquitously expressed in many tissues and cell types. It interacts specifically with the ligand for the transmembrane G protein-coupled receptors CXCR4 and CXCR7. The CXCL12/CXCR4 axis takes part in a series of physiological, biochemical, and pathological process, such as inflammation and leukocyte trafficking, cancer-induced bone pain, and postsurgical pain, and also is a key factor in the cross-talking between tumor cells and their microenvironment. Aberrant overexpression of CXCR4 is critical for tumor survival, proliferation, angiogenesis, homing and metastasis. In this review, we summarized the role of CXCL12/CXCR4 in cancer, CXCR4 inhibitors under clinical study, and natural product CXCR4 antagonists. In conclusion, the CXCL12/CXCR4 signaling is important for tumor development and targeting the pathway might represent an effective approach to developing novel therapy in cancer treatment.

A retrospective clinicopathological study of lung adenocarcinoma: Total tumor size can predict subtypes and lymph node involvement.

PURPOSE: To analyze the predictive ability of total tumor size in lung adenocarcinoma subtype and lymph node involvement. MATERIALS AND METHODS: 1018 patients, ≤3cm tumor, were enrolled. The maximum diameter and other variables of each tumor were measured. RESULTS: The optimal cut-off value for total tumor size in differentiating AIS and MIA from IAC was <1.15cm, in distinguishing lymph node involvement, it was 1.65cm. CONCLUSIONS: Total tumor size could be a reliable predictor of lung adenocarcinoma subtype and lymph node involvement irrespective of ground glass, part solid and solid characteristics.

[Establishment of A Clinical Prediction Model of Solid Solitary Pulmonary Nodules].

BACKGROUND: The solitary pulmonary nodule (SPN) is a common and challenging clinical problem, especially solid SPN. The object of this study was to explore the predictive factors of SPN appearing as pure solid with malignance and to establish a clinical prediction model of solid SPNs. METHODS: We had a retrospective review of 317 solid SPNs (group A) having a final diagnosis in the department of thoracic surgery, Shanghai Chest Hospital from January 2015 to December 2015, and analyzed their clinical data and computed tomography (CT) images, including age, gender, smoking history, family history of cancer, previous cancer history, diameter of nodule, nodule location (upper lobe or non-upper lobe, left or right), clear border, smooth margin, lobulation, spiculation, vascular convergence, pleural retraction sign, air bronchogram sign, vocule sign, cavity and calcification. By using univariate and multivariate analysis, we found the independent predictors of malignancy of solid SPNs and subsequently established a clinical prediction model. Then, another 139 solid SPNs with a final diagnosis were chosen in department of Cardiothoracic Surgery, Affiliated Zhoushan Hospital of Wenzhou Medical University as group B, and used to verify the accuracy of the prediction model. Receiver-operating characteristic (ROC) curves were constructed using the prediction model. RESULTS: Multivariate Logistic regression analysis was used to identify eight clinical characteristics (age, family history of cancer, previous cancer history, clear border, lobulation, spiculation, air bronchogram sign, calcification) as independent predictors of malignancy of in solid SPNs. The area under the ROC curve for our model (0.922; 95%CI: 0.865-0.961). In our model, diagnosis accuration rate was 84.89%. Sensitivity was 90.41%, and specificity was 78.79%, and positive predictive value was 80.50%, and negative predictive value was 88.14%. CONCLUSIONS: Our prediction model could accurately identify malignancy in patients with solid SPNs, thereby it can provide help for diagnosis of solid SPNs.