Impact of heart failure and preoperative platelet count on the postoperative short-term outcome in infective endocarditis patients.

BACKGROUND: Heart failure (HF) and platelet count are often considered risk factors for mortality in patients with infective endocarditis (IE); however, their effects on various complications have not been elucidated. HYPOTHESIS: We speculated that HF and platelet count have significant impact on the short-term outcomes of IE. METHODS: This single-center retrospective study analyzed data from 320 IE patients who underwent surgery. A multivariate Cox proportional hazards model was used to identify the risk factors for adverse outcomes. The effect of the platelet count on the prognosis of patients with HF was determined by subgroup analysis and Kaplan-Meier analysis. RESULTS: The study population was divided into the HF group (n = 102) and the non-HF group (n = 218). The median age of the total population was 44.5 years (31-56 years), of which 227 (70.94%) patients were male. The incidence rates of 1-year all-cause mortality, cardiac outcomes, and composite outcomes were respectively almost sixfold, fourfold, and threefold higher in the HF group than in the non-HF group (all p < 0.001). In multivariate Cox regression analysis, HF was an independent risk factor for 1-year all-cause mortality, cardiac outcomes, cerebral outcomes, and composite outcomes. The Kaplan-Meier survival curves revealed that the patients with both HF and thrombocytopenia demonstrated the worst composite outcomes than the patients of the other groups (log-rank p < 0.001). In the HF group, the platelet count was significantly associated with mortality and composite outcomes. CONCLUSIONS: HF and preoperative platelet count are significantly associated with 1-year all-cause mortality and adverse outcomes postoperatively in IE patients. Patients with HF and thrombocytopenia have the worst short-term prognosis.

Development and validation of a postoperative bleeding complications prediction model in infective endocarditis.

OBJECTIVES: Bleeding complications are one of the most serious postoperative complications after cardiac surgery and are associated with high mortality, especially in patients with infective endocarditis (IE). Our objectives were to identify the risk factors and develop a prediction model for postoperative bleeding complications in IE patients. METHODS: The clinical data of IE patients treated from October 2013 to January 2022 were reviewed. Multivariate logistic regression analysis was used to evaluate independent risk factors for postoperative bleeding complications and develop a prediction model accordingly. The prediction model was verified in a temporal validation cohort. The performance of the model was evaluated in terms of its discrimination power, calibration, precision, and clinical utility. RESULTS: A total of 423 consecutive patients with IE who underwent surgery were included in the final analysis, including 315 and 108 patients in the training cohort and validation cohort, respectively. Four variables were selected for developing a prediction model, including platelet counts, systolic blood pressure, heart failure and vegetations on the mitral and aortic valves. In the training cohort, the model exhibited excellent discrimination power (AUC = 0.883), calibration (Hosmer-Lemeshow test, P = 0.803), and precision (Brier score = 0.037). In addition, the model also demonstrated good discrimination power (AUC = 0.805), calibration (Hosmer-Lemeshow test, P = 0.413), and precision (Brier score = 0.067) in the validation cohort. CONCLUSIONS: We developed and validated a promising risk model with good discrimination power, calibration, and precision for predicting postoperative bleeding complications in IE patients.

Risk factors for mortality in surgical patients on combined continuous renal replacement therapy and extracorporeal membrane oxygenation: single-center retrospective study.

OBJECTIVE: In patients receiving extracorporeal membrane oxygenation (ECMO), continuous renal replacement therapy (CRRT) is increasingly being used for renal replacement and fluid management. However, critically ill surgical patients receiving combined ECMO and CRRT tend to have a high mortality rate, and there are limited studies on this population. Therefore, we aimed to investigate the risk factors for mortality in surgical patients receiving combined ECMO and CRRT. METHODS: Data of surgical patients who underwent ECMO between December 2013 and April 2023 were retrospectively reviewed. Univariate and multivariate logistic regression analysis were used to identify the risk variables. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff value of albumin and age to predict death. RESULTS: A total of 199 patients on ECMO support were screened, of which 105 patients were included in the final analysis. Of 105 patients, 77 (73.33%) were treated with CRRT. Veno-arterial ECMO was performed in 97 cases (92.38%), and the rest were veno-venous ECMO (n = 8, 7.62%). Cardiovascular-related surgery was performed in the main patients (n = 86, 81.90%) and other types of surgery in 19 patients. In surgical patients on ECMO support, the logistic regression analysis showed that CRRT implantation, male sex, and age were the independent risks factors for mortality. Furthermore, the ROC curve analysis showed that age 48.5 years had the highest Youden index. In surgical patients on combined CRRT and ECMO, age, valvular heart disease, and albumin were the independent risk factors for prognosis. Albumin had the highest Youden index at a cutoff value of 39.95 g/L for predicting mortality, though the overall predictive value was modest (area under ROC 0.704). Age had the highest Youden index at a cutoff value of 48.5 years for predicting mortality. CONCLUSIONS: In our cohort of surgical patients requiring ECMO, which consisted mostly of patients undergoing cardiovascular surgery requiring VA-ECMO, the need for CRRT was an independent risk factor for mortality. In the subset of patients on combined CRRT and ECMO, independent risk factors for mortality included higher age, lack of valvular heart disease, and lower serum albumin.

The prognostic significance and immune correlation of SLC10A3 in low-grade gliomas revealed by bioinformatic analysis and multiple immunohistochemistry.

PURPOSE: Despite the fact that genetic risk factors contribute to low-grade gliomas (LGGs), the role of critical genes as prognostic and theraputic biomarkers is quite limited. This study is designed to comprehensively investigate the prognostic role and predictive ability of solute carrier family 10 member 3 (SLC10A3) for immunotherapy in LGGs. METHODS: We analyzed the prognostic value of SLC10A3 from multiple datasets of LGG patients, and explored its immune correlation via multiple algorithms. Finally, we independently confirmed the clinical significance and its immune correlation using the multiplex staining assay of LGG samples on the tissue microarray. RESULTS: SLC10A3 mRNA was up-regulated in LGGs compared with normal brain tissues, and correlated with tumor grade, histological type, IDH wide type and non-codel 1p19q. Up-regulation of SLC10A3 transcription was remarkably associated with shortened overall survival time compared with down-regulation in TCGA, CGGA and Rembrandt datasets, and SLC10A3 exhibited good predictive ability for survival outcomes among LGGs. Correlation analyses showed that SLC10A3 mRNA expression correlates well with the six immune check points and immune cells. When the expression and immune correlation of SLC10A3 at the translational level were verified via multiplex immunohistochemistry, expression of SLC10A3 protein was higher in LGG compared with normal tissues, and expression of SLC10A3 protein was correlated well with macrophage, CD4 + T cell and B cell. CONCLUSIONS: Up-regulation of SLC10A3 mRNA is statistically associated with adverse survival outcomes and immune infiltration among LGGs. SLC10A3 might be a reliable survival predictor and a promising immunotherapy target for LGG patients.

Reduced Angiopoietin Factor 2 Levels Are Correlated with Better Cardiac Function and Prognosis in Valvular Heart Disease

ABSTRACT Introduction: There are few circulating biomarkers for valvular heart disease. Angiopoietin (Ang) 1, Ang2, and vascular endothelial growth factor are important inflammation-associated cytokines. The aim of this study was to investigate the clinical significance and association of Ang1, Ang2, and vascular endothelial growth factor in valvular heart disease. Methods: This is a retrospective study; a total of 62 individuals (valvular heart disease patients [n=42] and healthy controls [n=20]) were included. Plasma levels of Ang1, Ang2, and vascular endothelial growth factor were detected by enzyme-linked immunosorbent assays. We retrospectively collected the baseline characteristics and short-term outcomes; logistic regression was performed to identify predictor for short-term mortality. Results: Ang2 was significantly decreased in the valvular heart disease group compared with the healthy control group (P=0.023), while no significant difference was observed in the Ang1 and vascular endothelial growth factor levels. The Ang2 level of New York Heart Association (NYHA) I/II patients — but not NYHA III/IV patients — was significantly decreased compared with that of healthy control individuals (NYHA I/II: P=0.017; NYHA III/IV: P=0.485). Univariable logistic regression analysis indicated that Ang2 was a significant independent predictor for short-term mortality (odds ratio 18.75, P=0.033, 95% confidence interval 8.08-102.33). Ang1 was negatively correlated with Ang2 (P=0.032, Pearson's correlation coefficient =-0.317) and was positively correlated with vascular endothelial growth factor (P=0.019, Pearson's correlation coefficient = 0.359). Conclusion: Ang2 might serve as a therapeutic and prognostic target for valvular heart disease.

Reduced Angiopoietin Factor 2 Levels Are Correlated with Better Cardiac Function and Prognosis in Valvular Heart Disease.

INTRODUCTION: There are few circulating biomarkers for valvular heart disease. Angiopoietin (Ang) 1, Ang2, and vascular endothelial growth factor are important inflammation-associated cytokines. The aim of this study was to investigate the clinical significance and association of Ang1, Ang2, and vascular endothelial growth factor in valvular heart disease. METHODS: This is a retrospective study; a total of 62 individuals (valvular heart disease patients [n=42] and healthy controls [n=20]) were included. Plasma levels of Ang1, Ang2, and vascular endothelial growth factor were detected by enzyme-linked immunosorbent assays. We retrospectively collected the baseline characteristics and short-term outcomes; logistic regression was performed to identify predictor for short-term mortality. RESULTS: Ang2 was significantly decreased in the valvular heart disease group compared with the healthy control group (P=0.023), while no significant difference was observed in the Ang1 and vascular endothelial growth factor levels. The Ang2 level of New York Heart Association (NYHA) I/II patients - but not NYHA III/IV patients - was significantly decreased compared with that of healthy control individuals (NYHA I/II: P=0.017; NYHA III/IV: P=0.485). Univariable logistic regression analysis indicated that Ang2 was a significant independent predictor for short-term mortality (odds ratio 18.75, P=0.033, 95% confidence interval 8.08-102.33). Ang1 was negatively correlated with Ang2 (P=0.032, Pearson's correlation coefficient =-0.317) and was positively correlated with vascular endothelial growth factor (P=0.019, Pearson's correlation coefficient = 0.359). CONCLUSION: Ang2 might serve as a therapeutic and prognostic target for valvular heart disease.

Recent progress in fish oil-based emulsions by various food-grade stabilizers: Fabrication strategy, interfacial stability mechanism and potential application.

Fish oil, rich in a variety of long-chain ω-3 PUFAs, is widely used in fortified foods due to its broad-spectrum health benefits. However, its undesired characteristics include oxidation sensitivity, poor water solubility, and fishy off-flavor greatly hinder its exploitation in food field. Over the past two decades, constructing fish oil emulsions to encapsulate ω-3 PUFAs for improving their physicochemical and functional properties has undergone great progress. This review mainly focuses on understanding the fabrication strategies, stabilization mechanism, and potential applications of fish oil emulsions, including fish oil microemulsions, nanoemulsions, double emulsions, Pickering emulsions and emulsion gels. Furthermore, the role of oil-water interfacial stabilizers in the fish oil emulsions stability will be discussed with a highlight on food-grade single emulsifiers and natural complex systems for achieving this purpose. Additionally, its roles and applications in food industry and nutrition field are delineated. Finally, possible innovative food trends and applications are highlighted, such as novel fish oil-based delivery systems construction (e.g., Janus emulsions and nutraceutical co-delivery systems), exploring digestion and absorption mechanisms and enhancing functional evaluation (e.g., nutritional supplement enhancer, and novel fortified/functional foods). This review provides a reference for the application of fish oil-based emulsion systems in future precision diet intervention implementations.

Inhibitory Effect of Polypeptides Produced by Brevibacillus brevis on Ochratoxigenic Fungi in the Process of Pile-Fermentation of Post-Fermented Tea.

Contamination by ochratoxigenic fungi and its prevention during the pile-fermentation of post-fermented tea have always been a concern. The present study aimed to elucidate the anti-fungal effect and mechanism of polypeptides produced by B. brevis DTM05 (isolated from post-fermented tea) on ochratoxigenic fungi, and to to evaluate their use in the pile-fermentation process of post-fermented tea. The results showed that polypeptides (produced by B. brevis DTM05) with a strong antifungal effect against A. carbonarius H9 mainly had a molecular weight between 3 and 5 kDa. The Fourier-transform infrared spectra of this polypeptide extract showed that it was a mixture consisting mainly of polypeptides and small amounts of lipids and other carbohydrates. The polypeptide extracts significantly inhibited the growth of A. carbonarius H9, and its minimum inhibitory concentration (MIC) was 1.6 mg/L, which significantly reduced the survival rate of spores. The polypeptides also effectively controlled the occurrence and ochratoxin A (OTA) production of A. carbonarius H9 on the tea matrix. The lowest concentration of polypeptides that significantly inhibited the growth of A. carbonarius H9 on the tea matrix was 3.2 mg/L. The enhancement of the fluorescence staining signal in the mycelium and conidiospore showed that the polypeptides with a concentration of more than 1.6 mg/L increased the permeability of the mycelium membrane and conidial membrane of A. carbonarius H9. The significant increase in the extracellular conductivity of mycelia suggested the outward leakage of intracellular active substances, and also further indicated an increase in cell membrane permeability. Polypeptides with a concentration of 6.4 mg/L significantly down-regulated the expression level of the polyketide synthase gene related to OTA production (acpks) in A. carbonarius H9, which may be the fundamental reason why polypeptides affect OTA production. In conclusion, reasonable use of the polypeptides produced by B. brevis can destroy the structural integrity of the cell membrane, make the intracellular active substances leak outward, accelerate the death of fungal cells and down-regulate the expression level of the polyketide synthase gene in A. carbonarius; thus, they can effectively control the contamination of ochratoxigenic fungi and OTA production during the pile-fermentation of the post-fermented tea.

Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis.

AIM: Noninvasive evaluation of hypoxia in rabbit VX2 lung transplant tumors using spectral CT parameters and texture analysis. MATERIALS AND METHODS: Twenty-five VX2 lung transplant tumors of twenty-two rabbits were included in the study. Contrast-enhanced spectral CT scanning in the arterial phase (AP) and venous phase (VP) was performed. Tumors were divided into strong and weak hypoxic groups by hypoxic probe staining results. Spectral CT image-related parameters [70 keV CT value, normalized iodine concentration (NIC), slope of spectral HU curve (λHU)] were measured and the texture analysis on the monochromatic images was performed. Imaging parameters and texture features between tumors with different hypoxic degrees were compared and their diagnostic efficacies for predicting hypoxia in lung cancers were analyzed using receiver operating characteristic (ROC) curve. RESULTS: NIC in VP and λHU in VP of the strong hypoxic group were significantly higher than those in the weak hypoxic group (p < 0.05). For the texture features, entropy in VP and kurtosis in AP were significantly different between the two hypoxic groups. According to ROC analysis, λHU in VP had a better diagnostic ability for predicting hypoxia in tumors [Area Under Curve (AUC): 0.883, sensitivity: 85.7%, specificity: 100%]. The combination of four features improved AUC to 0.955. CONCLUSION: NIC in VP, λHU in VP, entropy in VP and kurtosis in AP have certain values in predicting tumor hypoxia and a combination of image parameters and texture features improves diagnostic efficiency.

Development and validation of a multivariable predictive model for EGFR gene mutation status in patients with lung adenocarcinoma.

Detection of epidermal growth factor receptor (EGFR) is one real dilemma owing to the non-sufficient tissue for testing EGFR mutations in lung adenocarcinoma. A model for predicting EGFR mutations would be helpful for clinical decisions in those patients. A retrospective cohort of 1,196 patients diagnosed with lung adenocarcinoma was investigated between December 1, 2017, and December 31, 2019, in Renji Hospital, Shanghai, China. All patients were tested for EGFR mutations (amplification refractory mutation system, n=1,144; next-generation sequencing, n=52). Of 1,196 patients with lung adenocarcinoma, 944 met the inclusion criteria. A nomogram model was developed based on 567 patients and validated in 377 patients. Variables associated with EGFR mutations were age, sex, smoking history, lepidic predominant subtype, solid predominant subtype, mucinous adenocarcinoma, Ki67 expression, lobulation, solid texture in radiology, and pleural retraction. The nomogram based on the model performed well in the development group (c-index 0.789, 95% CI: 0.751-0.827), and the validation group (c-index 0.809, 95% CI: 0.771-0.847). At the probability cut-point of 0.7, the diagnostic efficiency was 82.7% in patients with NGS liquid biopsy. Decision curve analysis further confirmed the clinical usefulness of the nomogram, which showed that predicting the EGFR mutations probability applying this nomogram would be better than having all patients or none patients use this nomogram. A high probability group (>0.7) by nomogram model may suggest a high possibility of EGFR mutation, if tissue is limited, NGS-based ctDNA with liquid biopsy could be implemented effectively.

Diffusion-weighted MRI and 18F-FDG PET/CT in assessing the response to neoadjuvant chemoradiotherapy in locally advanced esophageal squamous cell carcinoma.

BACKGROUND: Neoadjuvant chemoradiotherapy (nCRT) followed by surgery is a currently widely used strategy for locally advanced esophageal cancer (EC). However, the conventional imaging methods have certain deficiencies in the evaluation and prediction of the efficacy of nCRT. This study aimed to explore the value of functional imaging in predicting the response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced esophageal squamous cell carcinoma (ESCC). METHODS: Fifty-four patients diagnosed with locally advanced ESCC from August 2017 to September 2019 and treated with nCRT were retrospectively analyzed. DW-MRI scanning was performed before nCRT, at 10-15 fractions of radiotherapy, and 4-6 weeks after the completion of nCRT. 18F-FDG PET/CT scans were performed before nCRT and 4-6 weeks after the completion of nCRT. These 18F-FDG PET/CT and DW-MRI parameters and relative changes were compared between patients with pathological complete response (pCR) and non-pCR. RESULTS: A total of 8 of 54 patients (14.8%) were evaluated as disease progression in the preoperative assessment. The remaining forty-six patients underwent operations, and the pathological assessments of the surgical resection specimens demonstrated pathological complete response (pCR) in 10 patients (21.7%) and complete response of primary tumor (pCR-T) in 16 patients (34.8%). The change of metabolic tumor volume (∆MTV) and change of total lesion glycolysis (∆TLG) were significantly different between patients with pCR and non-pCR. The SUVmax-Tpost, MTV-Tpost, and TLG-Tpost of esophageal tumors in 18F-FDG PET/CT scans after neoadjuvant chemoradiotherapy and the ∆ SUVmax-T and ∆MTV-T were significantly different between pCR-T versus non-pCR-T patients. The esophageal tumor apparent diffusion coefficient (ADC) increased after nCRT; the ADCduring, ADCpost and ∆ADCduring were significantly different between pCR-T and non-pCR-T groups. ROC analyses showed that the model that combined ADCduring with TLG-Tpost had the highest AUC (0.914) for pCR-T prediction, with 90.0% and 86.4% sensitivity and specificity, respectively. CONCLUSION: 18F-FDG PET/CT is useful for re-staging after nCRT and for surgical decision. Integrating parameters of 18F-FDG PET/CT and DW-MRI can identify pathological response of primary tumor to nCRT more accurately in ESCC.

Determining the invasiveness of ground-glass nodules using a 3D multi-task network.

OBJECTIVES: The aim of this study was to determine the invasiveness of ground-glass nodules (GGNs) using a 3D multi-task deep learning network. METHODS: We propose a novel architecture based on 3D multi-task learning to determine the invasiveness of GGNs. In total, 770 patients with 909 GGNs who underwent lung CT scans were enrolled. The patients were divided into the training (n = 626) and test sets (n = 144). In the test set, invasiveness was classified using deep learning into three categories: atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive pulmonary adenocarcinoma (IA). Furthermore, binary classifications (AAH/AIS/MIA vs. IA) were made by two thoracic radiologists and compared with the deep learning results. RESULTS: In the three-category classification task, the sensitivity, specificity, and accuracy were 65.41%, 82.21%, and 64.9%, respectively. In the binary classification task, the sensitivity, specificity, accuracy, and area under the ROC curve (AUC) values were 69.57%, 95.24%, 87.42%, and 0.89, respectively. In the visual assessment of GGN invasiveness of binary classification by the two thoracic radiologists, the sensitivity, specificity, and accuracy of the senior and junior radiologists were 58.93%, 90.51%, and 81.35% and 76.79%, 55.47%, and 61.66%, respectively. CONCLUSIONS: The proposed multi-task deep learning model achieved good classification results in determining the invasiveness of GGNs. This model may help to select patients with invasive lesions who need surgery and the proper surgical methods. KEY POINTS: • The proposed multi-task model has achieved good classification results for the invasiveness of GGNs. • The proposed network includes a classification and segmentation branch to learn global and regional features, respectively. • The multi-task model could assist doctors in selecting patients with invasive lesions who need surgery and choosing appropriate surgical methods.

Preoperative Lymphocyte-to-Monocyte Ratio as a Prognostic Predictor of Long-Term Mortality in Cardiac Surgery Patients: A Propensity Score Matching Analysis.

Aims: To evaluate the prognostic value of the preoperative lymphocyte-to-monocyte ratio (LMR) in patients who underwent cardiac surgery. Methods: Clinical data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The optimal cutoff value of LMR was determined by X-tile software. The Cox proportional hazard model was applied for the identification of independent prognostic factors of 4-year mortality and survival curves were estimated using the Kaplan-Meier method. In order to balance the influence of potential confounding factors, a 1:1 propensity score matching (PSM) method was performed. Results: A total of 1,701 patients were included. The X-tile software indicated that the optimal cutoff value of the LMR for 4-year mortality was 3.58. After PSM, 489 pairs of score-matched patients were generated. The Cox proportional hazard model showed that patients with an LMR < 3.58 had a significantly higher 4-year mortality than patients with an LMR ≥ 3.58 in the entire cohort (HR = 1.925, 95%CI: 1.509-2.456, p < 0.001) and the PSM subset (HR = 1.568, 95%CI: 1.2-2.05, p = 0.001). The survival curves showed that patients with an LMR < 3.58 had a significant lower 4-year survival rate in the entire cohort (71.7 vs. 88.5%, p < 0.001) and the PSM subset (73.2 vs. 81.4%, p = 0.002). Conclusions: A lower LMR (<3.58) was associated with a higher risk of 4-year mortality and can serve as a prognostic predictor of the long-term mortality in cardiac surgery patients.

Determining the invasiveness of pure ground-glass nodules using dual-energy spectral computed tomography.

BACKGROUND: The present work aimed to investigate the clinical application of using quantitative parameters generated in the unenhanced phase (UP) and venous phase (VP) in dual-energy spectral CT for differentiating the invasiveness of pure ground-glass nodule (pGGN). METHODS: Sixty-two patients with 66 pGGNs who underwent preoperative dual-energy spectral CT in UP and VP were evaluated retrospectively. Nodules were divided into three groups based on pathology: adenocarcinoma in situ (AIS, n=19), minimally invasive adenocarcinoma (MIA, n=22) (both in the preinvasive lesion group) and invasive adenocarcinoma (IA, n=25). The iodine concentration (IC) and water content (WC) in nodules were measured in material decomposition images. The nodule CT numbers and slopes(k) were measured on monochromatic images. All measurements, including the maximum diameter of nodules were statistically compared between the AIS-MIA group and IA group. RESULTS: There were significant differences of WC in VP between AIS-MIA group and IA group (P<0.05). The CT attenuation values of the 40-140 keV monochromatic images in UP and VP were significantly higher for the invasive nodules. Logistic regression analysis showed that the maximum nodule diameter [odd ratio (OR) =1.21, 95% CI: 1.050-1.400, P<0.01] and CT number in 130 keV images in venous phase (OR =1.03, 95% CI: 1.014-1.047, P<0.001) independently predicted histological invasiveness. CONCLUSIONS: The quantitative parameters in dual-energy spectral CT in the unenhanced phase and venous phase provide useful information in differentiating preinvasive lesion group from IA group of pGGN, especially the maximum nodule diameter and CT number in the 130 keV images in the venous phase.

The associations among quantitative spectral CT parameters, Ki-67 expression levels and EGFR mutation status in NSCLC.

Dual-energy spectral computed tomography (DESCT) is based on fast switching between high and low voltages from view to view to obtain dual-energy imaging data, and it can generate monochromatic image sets, iodine-based material decomposition images and spectral CT curves. Quantitative spectral CT parameters may be valuable for reflecting Ki-67 expression and EGFR mutation status in non-small-cell lung cancer (NSCLC). We investigated the associations among the quantitative parameters generated in DESCT and Ki-67 expression and EGFR mutation in NSCLC. We studied sixty-five NSCLC patients with preoperative DESCT scans, and their specimens underwent Ki-67 and EGFR evaluations. Statistical analyses were performed to identify the spectral CT parameters for the diagnosis of Ki-67 expression and EGFR mutation status. We found that tumour grade and the slope of the spectral CT curve in the venous phase were the independent factors influencing the Ki-67 expression level, and the area under the curve (AUC) of the slope of the spectral CT curve in the venous phase in the receiver operating characteristic analysis for distinguishing different Ki-67 expression levels was 0.901. Smoking status and the normalized iodine concentration in the venous phase were independent factors influencing EGFR mutation, and the AUC of the two-factor combination for predicting the presence of EGFR mutation was 0.807. These results show that spectral CT parameters may be useful for predicting Ki-67 expression and the presence of EGFR mutation in NSCLC.

Preliminary exploration of survival analysis using the OHDSI common data model: a case study of intrahepatic cholangiocarcinoma.

BACKGROUND: Data heterogeneity is a common phenomenon related to the secondary use of electronic health records (EHR) data from different sources. The Observational Health Data Sciences and Informatics (OHDSI) Common Data Model (CDM) organizes healthcare data into standard data structures using concepts that are explicitly and formally specified through standard vocabularies, thereby facilitating large-scale analysis. The objective of this study is to design, develop, and evaluate generic survival analysis routines built using the OHDSI CDM. METHODS: We used intrahepatic cholangiocarcinoma (ICC) patient data to implement CDM-based survival analysis methods. Our methods comprise the following modules: 1) Mapping local terms to standard OHDSI concepts. The analytical expression of variables and values related to demographic characteristics, medical history, smoking status, laboratory results, and tumor feature data. These data were mapped to standard OHDSI concepts through a manual analysis; 2) Loading patient data into the CDM using the concept mappings; 3) Developing an R interface that supports the portable survival analysis on top of OHDSI CDM, and comparing the CDM-based analysis results with those using traditional statistical analysis methods. RESULTS: Our dataset contained 346 patients diagnosed with ICC. The collected clinical data contains 115 variables, of which 75 variables were mapped to the OHDSI concepts. These concepts mainly belong to four domains: condition, observation, measurement, and procedure. The corresponding standard concepts are scattered in six vocabularies: ICD10CM, ICD10PCS, SNOMED, LOINC, NDFRT, and READ. We loaded a total of 25,950 patient data records into the OHDSI CDM database. However, 40 variables failed to map to the OHDSI CDM as they mostly belong to imaging data and pathological data. CONCLUSIONS: Our study demonstrates that conducting survival analysis using the OHDSI CDM is feasible and can produce reusable analysis routines. However, challenges to be overcome include 1) semantic loss caused by inaccurate mapping and value normalization; 2) incomplete OHDSI vocabularies describing imaging data, pathological data, and modular data representation.

Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters.

Apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) has gained wide attention as potential tool for differentiating between malignant and benign solitary pulmonary lesions (SPLs). The overall effects of multiple histopathological parameters on ADC have not been elucidated, which may help to explain the overlapping of ADC between malignant and benign SPLs. The study sought to explore associations between ADC and histopathological parameters in SPLs, and to compare diagnostic capability of ADC among different types of SPLs. Multiple histopathological parameters (cell density, nuclear-to-cytoplasm ratio, necrotic fraction, presence of mucus and grade of differentiation) were quantified in 52 malignant and 13 benign SPLs with surgical pathology available. Cell density (ß = -0.40) and presence of mucus (ß = 0.77) were independently correlated with ADC in malignant SPLs. The accurate diagnosis rate of squamous carcinomas, adenocarcinomas without mucus and malignant tumors with mucus was 100%, 82% and 0%, respectively. Our study suggested that cell density and presence of mucus are independently correlated with ADC in malignant SPLs. Squamous carcinoma maybe more accurately diagnosed as malignancy by ADC value. Malignant SPLs with mucus and adenocarcinomas with low cell density should be kept in mind in differentiating SPLs using ADC because of insufficient diagnostic capability.

Analysis of pulmonary pure ground-glass nodule in enhanced dual energy CT imaging for predicting invasive adenocarcinoma: comparing with conventional thin-section CT imaging.

BACKGROUND: To investigate the value of dual energy computed tomography (DECT) parameters (including iodine concentration and monochromatic CT numbers) for predicting pure ground-glass nodules (pGGNs) of invasive adenocarcinoma (IA). METHODS: A total of 55 resected pGGNs evaluated with both unenhanced thin-section CT (TSCT) and enhanced DECT scans were included. Correlations between histopathology [adenocarcinoma in situ (AIS), minimally IA (MIA), and IA] and CT scan characteristics were examined. CT scan and clinicodemographic data were investigated by univariate and multivariate analysis to identify features that helped distinguish IA from AIS or MIA. RESULTS: Both normalized iodine concentration (NIC) of IA and slope of spectral curve [slope(k)] were not significantly different between IA and AIS or MIA. Size, performance of pleural retraction and enhanced monochromatic CT attenuation values of 120-140 keV were significantly higher for IA. In multivariate regression analysis, size and enhanced monochromatic CT number of 140 keV were independent predictors for IA. Using the two parameters together, the diagnostic capacity of IA could be improved from 0.697 or 0.635 to 0.713. CONCLUSIONS: DECT could help demonstrate blood supply and indicate invasion extent of pGGNs, and monochromatic CT number of higher energy (especially 140 keV) would be better for diagnosing IA than lower energies. Together with size of pGGNs, the diagnostic capacity of IA could be better.

Assessment of Heterogeneity Difference Between Edge and Core by Using Texture Analysis: Differentiation of Malignant From Inflammatory Pulmonary Nodules and Masses.

RATIONALE AND OBJECTIVES: This study aimed to test the hypothesis that the heterogeneity difference between edge and core of lesions by using intensity and entropy features obtained from whole-lesion texture analysis on contrast-enhanced computed tomography (CT) may be useful for differentiation of malignant from inflammatory pulmonary nodules and masses. MATERIALS AND METHODS: In all, 48 single pulmonary nodules and masses were retrospectively evaluated. All lesions were histologically or clinically confirmed (malignancy: inflammation = 24:20). We utilized a newly introduced texture analysis method based on contrast-enhanced CT (first described by Grove et al.) that automatically divided the whole lesion volume into two regions: edge and core. Mean attenuation value (AV) and entropy of each region and also the whole lesion were evaluated separately. Each texture metric (absolute value for each region, and difference value defined as difference between edge and core) of malignant and inflammatory lesions were compared using Mann-Whitney U test. Individual image parameters were combined by using linear discriminant analysis. Receiver operating characteristic curves were generated to assess each texture metric and their combination for discriminating between the two entities. RESULTS: Mean AV difference and entropy difference were significantly higher in malignant lesions than in inflammatory lesions (4.71 HU ± 5.06 vs -1.53 HU ± 5.05, P < .001; 0.45 ± 0.23 vs 0.18 ± 0.30, P = .001). Receiver operating characteristic curves for individual mean AV difference and entropy difference provided relatively high values for the area under the curve (0.836 and 0.795, respectively). The combination of mean AV difference, entropy difference, and lesion volume improved the area under the curve to 0.864. CONCLUSION: Heterogeneity difference between edge and core by using whole-lesion texture analysis on contrast-enhanced CT may be a promising tool for estimating the probability of malignancy in pulmonary nodules and masses.

Can Spectral CT Imaging Improve the Differentiation between Malignant and Benign Solitary Pulmonary Nodules?

PURPOSE: To quantitatively assess the value of dual-energy CT (DECT) in differentiating malignancy and benignity of solitary pulmonary nodules. MATERIALS AND METHODS: Sixty-three patients with solitary pulmonary nodules detected by CT plain scan underwent contrast enhanced CT scans in arterial phase (AP) and venous phase (VP) with spectral imaging mode for tumor type differentiation. The Gemstone Spectral Imaging (GSI) viewer was used for image display and data analysis. Region of interest was placed on the relatively homogeneous area of the nodule to measure iodine concentration (IC) on iodine-based material decomposition images and CT numbers on monochromatic image sets to generate spectral HU curve. Normalized IC (NIC), slope of the spectral HU curve (λHU) and net CT number enhancement on 70keV images were calculated. The two-sample t-test was used to compare quantitative parameters. Receiver operating characteristic curves were generated to calculate sensitivity and specificity. RESULTS: There were 63 nodules, with 37 malignant nodules (59%) and 26 benign nodules (41%). NIC, λHU and net CT number enhancement on 70keV images for malignant nodules were all greater than those of benign nodules. NIC and λHU had intermediate to high performances to differentiate malignant nodules from benign ones with the areas under curve of 0.89 and 0.86 respectively in AP, 0.96 and 0.89 respectively in VP. Using 0.30 as a threshold value for NIC in VP, one could obtain sensitivity of 93.8% and specificity of 85.7% for differentiating malignant from benign solitary pulmonary nodules. These values were statistically higher than the corresponding values of 74.2% and 53.8% obtained with the conventional CT number enhancement. CONCLUSIONS: DECT imaging with GSI mode provides more promising value in quantitative way for distinguishing malignant nodules from benign ones than CT enhancement numbers.